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Full text of "Differential & Integral Calculus Vol I"

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R. COURANT 


BLACKIE 


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DIFFERENTIAL AND 
INTEGRAL CALCULUS 

by R. COURANT 
Volume I 

A novel and masterly text- book on the 
Calculus for students of Mathematics, 
Physical Science, or Engineering. The 
author, a mathematical writer of interna- 
tional repute, has aimed at avoiding the 
two extremes of slipshodncss and repellent 
formalism. By skilful arrangement of the 
material and suitable use of intuition he 
has succeeded in combining accuracy with 
unusual attractiveness of presentation. 



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DIFFERENTIAL AND 
INTEGRAL CALCULUS 



BLACKIE & SON LIMITED 

16/18 William IV Street, Charing Cross, London, W.Ga 

17 Stanhope Street, Glascow 

BLACKIE & SON (INDIA) LIMITED 
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BLACKIE & SON (CANADA) LIMITED 
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DIFFERENTIAL AND 
INTEGRAL CALCULUS 



BY 
R. COURANT 

Professor of Mathematics in New York University 
TRANSLATED BY 

E. J. McSHANE 

Professor of Mathematics in the University of Virginia 



VOLUME I 



fEGQNTf EDITION 


• 


. 1 


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> 




BLACKIE & SON LIMITED 

LONDON AND GLASGOW 



First published 1934 

Second edition 1937 

Reprinted 1940, 194', '942 {twice) 

1943, J944, 1945, X946, 1947, K)4S 
'949, '950, I9S 1 , 195*, "953, 1954 
I 9SS, I 9S ( > (twice), 1957 (twice) 
Z938, 1959, i960, 1961 



Printed in Great Britain by Blackie & Son, Ltd., Glasgoa 



PREFACE 
TO THE FIRST GERMAN EDITION 



Although there is no lack of textbooks on the differential and 
integral calculus, the beginner will have difficulty in finding a 
book that leads him straight to the heart of the subject and gives 
him the power to apply it intelligently. He refuses to be bored 
by diffuseness and general statements which convey nothing to 
him, and will not tolerate a pedantry which makes no distinction 
between the essential and the non-essential, and which, for the 
sake of a systematic set of axioms, deliberately conceals the 
facts to which the growth of the subject is due. 

True, it is easier to perceive defects than to remedy them. 
I make no claim to have presented the beginner with the ideal 
textbook. Yet I do not consider the publication of my lectures 
superfluous. In order and choice of material, in fundamental 
aim, and perhaps also in mode of presentation, they differ con- 
siderably from the current literature. 

The reader will notice especially the complete break away 
from the out-of-date tradition of treating the differential calculus 
and the integral calculus separately. This separation, a mere 
result of historical accident, with no good foundation either in 
theory or in practical convenience in teaching, hinders the 
student from grasping the central point of the calculus, namely, 
the connexion between definite integral, indefinite integral, and 
derivative. With the backing of Felix Klein and others, the 
simultaneous treatment of differential calculus and integral 
calculus has steadily gained ground in lecture courses. I here 
attempt to give it a place in the literature. This first volume 
deals mainly with the integral and differential calculus for func- 
tions of one variable; a second volume will be devoted to 
functions of several variables and some other extensions of the 
calculus. 



vi PREFACE TO THE FIRST GERMAN EDITION 

My aim is to exhibit the close connexion between analysis and 
its applications and, without loss of rigour and precision, to give 
due credit to intuition as the source of mathematical truth. 
The presentation of analysis as a closed system of truths without 
reference to their origin and purpose has, it is true, an aesthetic 
charm and satisfies a deep philosophical need. But the attitude 
of those who consider analysis solely as an abstractly logical, 
introverted science is not only highly unsuitable for beginners 
but endangers the future of the subject; for to pursue mathe- 
matical analysis while at the same time turning one's back on its 
applications and on intuition is to condemn it to hopeless atrophy. 
To me it seems extremely important that the student should be 
warned from the very beginning against a smug and presumptu- 
ous purism; this is not the least of my purposes in writing this 
book. 

The book is intended for anyone who, having passed through 
an ordinary course of school mathematics, wishes to apply him- 
self to the study of mathematics or its applications to science 
and engineering, no matter whether he is a student of a univer- 
sity or technical college, a teacher, or an engineer. I do not 
promise to save the reader the trouble of thinking, but I do seek 
to lead the way straight to useful knowledge, and aim at making 
the subject easier to grasp, not only by giving proofs step by 
step, but also by throwing light on the interconnexions and 
purposes of the whole. 

The beginner should note that I have avoided blocking the 
entrance to the concrete facts of the differential and integral 
calculus by discussions of fundamental matters, for which he is 
not yet ready. Instead, these are collected in appendices to the 
chapters, and the student whose main purpose is to acquire the 
facts rapidly or to proceed to practical applications may post- 
pone reading these until he feels the need for them. The appen- 
dices also contain some additions to the subject-matter; they 
have been made relatively concise. The reader will notice, too, 
that the general style of presentation, at first detailed, is more 
condensed towards the end of the book. He should not, however 
let himself be disheartened by isolated difficulties which he 
may find in the concluding chapters. Such gaps in understand- 
ing, if not too frequent, usually fill up of their own accord. 



PREFACE TO THE ENGLISH EDITION 



When American colleagues urged me to publish an English 
edition of my lectures on the differential and integral calculus, 
I at first hesitated. I felt that owing to the difference between 
the methods of teaching the calculus in Germany and in Britain 
and America a simple translation was out of the question, and 
that fundamental changes would be required in order to meet 
the needs of English-speaking students. 

My doubts were not laid to rest until I found a competent 
colleague in Professor E. J. McShane, of the University of 
Virginia, who was prepared not only to act as translator but also 
— after personal consultation with me — to make the improve- 
ments and alterations necessary for the English edition. 

Apart from many matters of detail the principal changes are 
these: (1) the English edition contains a large number of classified 
examples; (2) the division of material between the two volumes 
differs somewhat from that in the German text. In addition to 
a detailed account of the theory of functions of one variable, 
the present volume contains (in Chapter X) a sketch of the 
differentiation and integration of functions of several variables. 
The second volume deals in full with functions of several inde- 
pendent variables, and includes the elements of vector analysis. 
There is also a more systematic discussion of differential equa- 
tions, and an appendix on the foundations of the theory of real 
numbers. 

Thus the first volume contains the material for a course in 
elementary calculus, while the subject-matter of the second 
volume is more advanced. In the first volume, however, there is 
much which should be omitted from a first course. These sec- 
tions, intended for students wishing to penetrate more deeply 
into the theory, are collected in the appendices to the chapters, 

'• vii (a 788) 



viii PREFACE TO THE ENGLISH EDITION 

so that beginners can study the book without inconvenience, 
omitting or postponing the reading of these appendices. 

The publication of this book in English has only been made 
possible by the generosity of my German publisher, Julius 
Springer, Berlin, to whom I wish to express my most cordial 
thanks. I have likewise to thank Blackie and Son, Ltd., who 
in spite of these difficult times have undertaken to publish this 
edition. My special thanks are due to the members of their 
technical staff for the excellent quality of their work, and to 
their mathematical editors, especially Miss W. M. Deans, who 
have relieved Prof. McShane and myself of much of the respon- 
sibility of preparing the manuscript for the press and reading 
the proofs. I am also indebted to many friends and colleagues, 
notably to Professor McClenon of Grinnell College, Iowa, to 
whose encouragement the English edition is due; and to Miss 
Margaret Kennedy, Newnham College, Cambridge, and Dr. 
Fritz John, who co-operated with the publisher's staff in the 
proof-reading. 

R. COURANT. 
Cambridge, England, 
June, 1934. 



PREFACE 
TO THE SECOND ENGLISH EDITION 

This second edition differs from the first chiefly in the 
improvement and rearrangement of the examples, the addi- 
tion of many new examples at the end of the book, and the 
inclusion of some additional material on differential equations. 

R. COURANT. 

New Rochellb, N.V.. 
June, 1937. 



CONTENTS 



Iktboduotory Remarks ..... 1 

Chapter I 
INTRODUCTION 

1. The Continuum of Numbers ...... 6 

2. The Concept of Function 14 

3. More Detailed Study of the Elementary Functions - • 22 

4. Functions of an Integral Variable. Sequences of Numbers • 27 

5. The Concept of the Limit of a Sequence ----- 29 

6. Further Discussion of the Concept of Limit .... 38 

7. The Concept of limit where the Variable is Continuous - • 46 

8. The Concept of Continuity 49 

APPENDIX I 

Preliminary Remarks 56 

1. The Principle of the Point of Accumulation and its Applications - 58 

2. Theorems on Continuous Functions ----- • 63 

3. Some Remarks on the Elementary Functions .... 68 

APPENDIX II 

1. Polar Co-ordinates 71 

2. Remarks on Complex Numbers 73 

Chaptbb n 

THE FUNDAMENTAL DDEAS OF THE INTEGRAL 
AND DDJFERENTIAL CALCULUS 

1. The Definite Integral 76 

2. Examples 82 



x CONTENTS 

Page 

3. The Derivative 88 

4. The Indefinite Integral, the Primitive Function, and the Funda- 

mental Theorems of the Differential and Integral Calculus - 109 

5. Simple Methods of Graphical Integration 119 

6. Further Remarks on the Connexion between the Integral and the 

Derivative - ...... 121 

7. The Estimation of Integrals and the Mean Value Theorem of the 

Integral Calculus 126 

APPENDIX 

1. The Existence of the Definite Integral of a Continuous Function 131 

2. The Relation between the Mean Value Theorem of the Differential 

Calculus and the Mean Value Theorem of the Integral Cal- 
culus ....-••••• 134 

Chapter HI 

DIFFERENTIATION AND INTEGRATION OF THE 
ELEMENTARY FUNCTIONS 

1. The Simplest Rules for Differentiation and their Applications - 136 

2. The Corresponding Integral Formulae 141 

3. The Inverse Function and its Derivative 144 

4. Differentiation of a Function of a Function .... 153 

5. Maxima and Minima - 158 

6. The Logarithm and the Exponential Function .... 167 

7. Some Applications of the Exponential Function • • - 178 

8. The Hyperbolic Functions 183 

9. The Order of Magnitude of Functions 189 

APPENDIX 

1. Some Special Functions 196 

2. Remarks on the Differentiability of Functions • • • -199 

3. Some Special Formulae 201 

Chapter IV 

FURTHER DEVELOPMENT OF THE INTEGRAL 
CALCULUS 

1. Elementary Integrals 205 

2. The Method of Substitution 207 



CONTENTS xi 

Page 

3. Further Examples of the Substitution Method .... 214 

4. Integration by Parts 218 

6. Integration of Rational Functions ...... 226 

6. Integration of Some Other Classes of Functions .... 234 

7. Remarks on Functions which are not Integrable in Terms of 

Elementary Functions .... - 242 

8. Extension of the Concept of Integral. Improper Integrals • • 245 



APPENDIX 
The Second Mean Value Theorem of the Integral Calculus • • 258 

Chapter V 
APPLICATIONS 



1. Representation of Curves - - - • . 

2. Applications to the Theory of Plane Curves 

3. Examples 

4. Some very Simple Problems in the Mechanics of a Particle 

5. Further Applications: Particle sliding down a Curve - 

6. Work ......... 



258 
267 
287 
292 
299 
304 



APPENDIX 

1. Properties of the Evolute 307 

2. Areas bounded by Closed Curves 311 



Chapter VI 

TAYLOR'S THEOREM AND THE APPROXIMATE 
EXPRESSION OF FUNCTIONS BY POLYNOMIALS 

1. The Logarithm and the Inverse Tangent .... 315 

2. Taylor's Theorem 320 

3. Applications. Expansions of the Elementary Functions - - 326 

4. Geometrical Applications • • - • ■ - - 331 



xii CONTENTS 

APPENDIX 

Page 

1. Example of a Function which cannot be expanded in a Taylor 

Series .......... 336 

2. Proof that e is Irrational ....... 336 

3. Proof that the Binomial Series Converges 337 

4. Zeros and Infinities of Functions, and So-called Indeterminate 

Expressions ......... 338 

Chapter VII 
NUMERICAL METHODS 

Preliminary Remarks ........ 342 

1. Numerical Integration ........ 342 

2. Applications of the Mean Value Theorem and of Taylor's Theorem. 

The Calculus of Errors 349 

3. Numerical Solution of Equations 355 

APPENDIX 
Stirling's Formula 361 

Chapter Vlll 
INFINITE SERIES AND OTHER LIMITING PROCESSES 

Preliminary Remarks ........ 365 

1. The Concepts of Convergence and Divergence .... 366 

2. Tests for Convergence and Divergence 377 

3. Sequences and Series of Functions ...... 383 

4. Uniform and Non-uniform Convergence ..... 386 

5. Power Series 398 

6. Expansion of Given Functions in Power Series. Method of 

Undetermined Coefficients. Examples .... 404 

7. Power Series with Complex Terms 410 

APPENDIX 

1. Multiplication and Division of Series ..... 415 

2. Infinite Series and Improper Integrals ..... 417 

3. Infinite Products 419 

4. Series involving Bernoulli's Numbers 422 



CONTENTS siii 

Chapter IX 
FOURIER SERIES 

Page 

1. Periodic Functions ......... 425 

2. Use of Complex Notation 433 

3. Fourier Series 437 

4. Examples of Fourier Series 440 

5. The Convergence of Fourier Series ...... 447 

APPENDIX 

Integration of Fourier Series ---.... 455 

Chapter X 

A SKETCH OF THE THEORY OF FUNCTIONS OF 
SEVERAL VARIABLES 

1. The Concept of Function in the Case of Several Variables - • 458 

2. Continuity .......... 453 

3. The Derivatives of a Function of Several Variables - . . 466 

4. The Chain Rule and the Differentiation of Inverse Functions - 472 

5. Implicit Functions ......... 4go 

6. Multiple and Repeated Integrals 486 

Chapter XI 

THE DIFFERENTIAL EQUATIONS FOR THE SIMPLEST 
TYPES OF VIBRATION 

1. Vibration Problems of Mechanics and Physics .... 502 

2. Solution of the Homogeneous Equation. Free Oscillations - 504 

3. The Non-homogeneous Equation. Forced Oscillations - - 509 

4. Additional Remarks on Differential Equations - . . 519 

Summary car Important Theorems and Formulae - . 529 

Miscellaneous Examples 549 

Answers and Hints ........ 571 

Index 611 



DIFFERENTIAL AND 
INTEGRAL CALCULUS 



Introductory Remarks 

When the beginner comes in contact with the so-called higher 
mathematics for the first time, he is apt to be obsessed by the 
feeling that there is a certain discontinuity between school 
mathematics and university mathematics. This feeling ulti- 
mately rests on more than the historical circumstances which 
have caused university teaching to take a form differing so widely 
from that of the school. For the very nature of the higher 
mathematics, or rather, of the modern mathematics, developed 
during the last three centuries, distinguishes it from the elemen- 
tary mathematics which wholly dominated the school curri- 
culum until recently and whose subject-matter was often taken 
over almost directly from the mathematics of the ancient 
Greeks. 

A leading characteristic of elementary mathematics is its 
intimate association with geometry. Even where the subject 
passes beyond the realm of geometry into that of arithmetic, 
the fundamental ideas still remain geometrical. Another feature 
of ancient mathematics is perhaps its tendency to concentrate 
on particular cases. Things which to-day we should regard as 
special cases of a general phenomenon are set down higgledy- 
piggledy without any visible relationship between them. Its 
intimate association with geometrical ideas and its stress on 
individual niceties give the older mathematics a charm of its 
own. Yet it was a definite advance when at the beginning of 
the modern age in mathematics quite different tendencies de- 



a INTRODUCTORY REMARKS 

veloped, acting as the stimulus for a great expansion of tbe 
subject, which in spite of many improvements in detail had 
in a sense stood still for centuries. 

The fundamental tendency of all modem mathematics is 
towards the replacement of separate discussions of individual 
cases by more and more general systematic methods, which 
perhaps do not always do full justice to the individual features 
of a particular case, but which, owing to their generality and 
power, give promise of a wealth of new results. Again, the con- 
cept of number and the methods of analysis have come to occupy 
more and more independent positions and now dominate geometry 
entirely. These new tendencies towards the development of 
mathematics along a variety of lines are most clearly exhibited 
in the rise of analytical geometry, whose development is chiefly 
due to Fermat and Descartes, and of the differential and integral 
calculus, which is generally regarded as having originated with 
Newton and Leibnitz. 

The three hundred years during which modern mathematics 
has existed have seen such important advances not only in pure 
mathematics, but in an immense variety of applications to 
science and engineering, that its fundamental ideas and above 
all the concept of a function have by degrees become very widely 
known and have eventually penetrated even into the school 
curriculum. 

In this book my aim has been to develop the most important 
facts in the differential and integral calculus so far that at the close 
the reader, although he may have had no previous knowledge of 
higher mathematics, may be well equipped on the one hand for 
the study of the more advanced branches and of the foundations 
of the subject, or on the other hand, for the manipulation of the 
calculus in the varied realms in which it is applied. 

I should like to warn the reader specially against a danger 
which arises from the discontinuity mentioned in the opening 
paragraph. The point of view of school mathematics tempts one 
to linger over details and to lose one's grasp of general relation- 
ships and systematic methods. On the other hand, in the 
" higher " point of view there lurks the opposite danger of 
getting out of touch with concrete details, so that one is left 
helpless when faced with the simplest cases of individual difficulty, 
because in the world of general ideas one has forgotten how to 



INTRODUCTORY REMARKS 3 

come to grips with the concrete. The reader must find his own 
way of meeting this dilemma. In this he can only succeed by 
repeatedly thinking out particular cases for himself and acquiring 
a firm grasp of the application of general principles in particular 
cases; herein lies the chief task of anyone who wishes to pursue 
the study of Science. 



CHAPTER I 
Introduction 

The differential and integral calculus ia based upon two 
concepts of outstanding importance, apart from the concept of 
number, namely, the concept of function and the concept of 
limit. These concepts can, it is true, be recognized here and 
there even in the mathematics of the ancients, but it is only 
in modern mathematics that their essential character and signi- 
ficance are fully brought out. In this introductory chapter 
we shall attempt to explain these concepts as simply and 
clearly as possible. 

1. The Continuum of Numbers 

The question as to the real nature of numbers is one which 
concerns philosophers more than mathematicians, and philo- 
sophers have been much occupied with it. But mathematics 
must be carefully kept free from conflicting philosophical 
opinions; preliminary study of the essential nature of the con- 
cept of number from the point of view of the theory of know- 
ledge is fortunately not required by the student of mathematics. 
We shall therefore take the numbers, and in the first place the 
natural numbers 1, 2, 3, . . ., as given, and we shall likewise 
take as given the rules* by which we calculate with these 
numbers; and we shall only briefly recall the way in which the 
concept of the positive integers (the natural numbers) has had 
to be extended. 

* These rules are as follows: (o + 6) + c - o + (6 + 6). That is, if to the 
sum of two numbers a and b we add a third number c, we obtain the same 
result as when we add to a the sum of 6 and c. (This is called the associative 
law of addition.) Secondly, a + b = b + a (the commutative law of addition). 
Thirdly, (ab)c = a(bc) (the associative law of multiplication). Fourthly, ab = ba 
(the commutative law of multiplication). Fifthly, a(b + c) - ab + ac (the 
distributive law of multiplication). 

6 



6 INTRODUCTION [Chap. 

1. The System of Rational Numbers and the Need for its 
Extension. 

In the domain of the natural numbers the fundamental 
operations of addition and multiplication can always be per- 
formed without restriction; that is, the sum and the product of 
two natural numbers are themselves always natural numbers. 
But the inverses of these operations, subtraction and division, 
cannot invariably be performed within the domain of natural 
numbers; and because of this mathematicians were long ago 
obliged to invent the number 0, the negative integers, and 
positive and negative fractions. The totality of all these numbers 
is usually called the class of rational numbers, since they are all 
obtained from unity by using the " rational operations of calcu- 
lation ", addition, multiplication, 

jj — J z _j J — j — + — +~- subtraction and division. 

Fig. ..-The number axU Numbers are usually represented 

graphically by means of the points 
of a straight line, the " number axis ", by taking an arbitrary 
point of the line as the origin or zero point and another 
arbitrary point as the point 1; the distance between these two 
points (the length of the unit interval) then serves as a scale by 
which we can assign a point on the line to every rational number, 
positive or negative. It is customary to mark off the positive 
numbers to the right and the negative numbers to the left 
of the origin (cf. fig. 1). If, as usual, we define the absolute 
value (also called the numerical value or modulus) | a | of 
a number a to be a itself when * a Si 0, and to be — a when 
a < 0, then | a | simply denotes the distance of the corresponding 
point on the number axis from the origin. 

The geometrical representation of the rational numbers by 
points on the number axis suggests an important property which 
is usually stated as follows: the set of rational numbers is every- 
where dense. This means that in every interval of the number 
axis, no matter how small, there are always rational numbers; 
geometrically, in the segment of the number axis between any 
two rational points, no matter how close together, there are points 
corresponding to rational numbers. This density of the rational 

* By the sign ^ we mean that either the sign > or the sign — shall hold. 
A corresponding statement holds for the signs ± and T which will be used 
later. 



I] THE CONTINUUM OF NUMBERS 7 

numbers at once becomes clear if we start from the fact that the 

numbers -, — , — _, . . . become steadily smaller and 

approach nearer and nearer to zero as » increases. If we now 

divide the number axis into equal parts of length 1/2", beginning 

12 3 
at the origin, the end-points — , _,_,... of these intervals 

2" 2" 2" 

represent rational numbers of the form m/2"; here we still have 

the number n at our disposal. If now we are given a fixed 

interval of the number axis, no matter how small, we need only 

choose n so large that 1/2" is less than the length of the interval; 

the intervals of the above subdivision are then small enough for 

us to be sure that at least one of the points of subdivision m/2 n 

lies in the interval. 

Yet in spite of this property of density the rational numbers 
are not sufficient to represent every point on the number axis. 
Even the Greek mathematicians recognized that when a given 
line segment of unit length is chosen there are intervals whose 
lengths cannot be represented by rational numbers; these are 
the so-called segments incommensurable with the unit. Thus, for 
example, the hypotenuse of a right-angled isosceles triangle with 
sides of unit length is not commensurable with the unit of length. 
For, by the theorem of Pythagoras, the square of this length I 
must be equal to 2. Therefore, if I were a rational number 
and consequently equal to p/q, where p and q are integers 
different from 0, we should have p* = 2q\ We can assume that 
p and q have no common factors, for such common factors could 
be cancelled out to begin with. Since, according to the above 
equation, p 2 is an even number, p itself must be even, say 
p = 2p'. Substituting this expression for p gives us 4p' 2 = 2q\ 
or q* = 2p' 2 ; consequently q* is even, and so q is also even. 
Hence p and q both have the factor 2. But this contradicts our 
hypothesis that p and q have no common factor. Thus the 
assumption that the hypotenuse can be represented by a fraction 
p/q leads to contradiction and is therefore false. 

The above reasoning, which is a characteristic example of 
an " indirect proof ", shows that the symbol ^2 cannot corre- 
spond to any rational number. Thus we see that if we insist that 
after choice of a unit interval every point of the number axis 
shall have a number corresponding to it, we are forced to extend 



8 INTRODUCTION [Chap 

the domain of rational numbers by the introduction of new 
" irrational " numbers. This system of rational and irrational 
numbers, such that each point on the axis corresponds to just 
one number and each number corresponds to just one point on 
the axis, is called the system of real numbers.* 

2. Real Numbers and Infinite Decimals. 

Our requirement that to each point of the axis there shall 
correspond one real number states nothing a priori about the 
possibility of calculating with these real numbers in the same 
way as with rational numbers. We establish our right to do 
this by showing that our requirement is equivalent to the 
following fact: the totality of all real numbers is represented 
by the totality of all finite and infinite decimals. 

We first recall the fact, familiar from elementary mathe- 
matics, that every rational number can be represented by a 
terminating or by a recurring decimal; and conversely, that every 
such decimal represents a rational number. We shall now show 
that to every point of the number axis we can assign a uniquely 
determined decimal (usually infinite), so that we can represent 
the irrational points or irrational numbers by infinite decimals. 
(In accordance with the above remark the irrational numbers 
must be represented by infinite non-recurring decimals, for ex- 
ample, 0-101101110 . . .). 

Suppose that the points which correspond to the integers 

are marked on the number axis. By means of these points the 

axis is subdivided into intervals or segments of length 1. In 

what follows, we shall say that a point of the line belongs to an 

interval if it is an interior point or an end-point of the interval. 

Now let P be an arbitrary point of the number axis. Then the 

point belongs to one, or if it is a point of division to two, of 

the above intervals. If we agree that in the second case the 

right-hand one of the two intervals meeting at P is to be chosen, 

we have in all cases an interval with end-points g and g -f- 1 to 

which P belongs, where g is an integer. This interval we 

subdivide into ten equal sub-intervals by means of the points 

12 9 

corresponding to the numbers g + — , g -\- — , . . . , g -\- — , and 

* Thus named to distinguish it from the system of complex numbers, obtained 
by yet another extension. 



I] THE CONTINUUM OF NUMBERS 9 

we number these sub-intervals 0, 1, . . . , 9 in the natural order 
from left to right. The sub-interval with the number a then has 

the end-points g 4- — and g 4- — 4- — . The point P must be 

contained in one of these sub-intervals. (If P is one of the new 
points of division it belongs to two consecutive intervals; as 
before, we choose the one on the right.) Suppose that the interval 
thus determined is associated with the number Oj. The end- 
points of this interval then correspond to the numbers g 4- — 
and g 4- ^ 4- — . This sub-interval we again divide into ten 

equal parts and determine that one to which P belongs; as be- 
fore, if P belongs to two sub-intervals we choose the one on the 
right. We thus obtain an interval with the end-points 

9 + w + w» and 9 + w + W + W where " 2 i8 one of the 

digits 0, 1, . . . , 9. This sub-interval we again subdivide, and 
continue to repeat the process. After n steps we arrive at a sub- 
interval containing P, having length — and with end-points 
corresponding to the numbers 

Here each a is one of the numbers 0, 1, . . . , 9. But 

10 10 2 " 10" 
is simply the decimal fraction O-o^ ■ . . a„. The end-points 
of the interval, therefore, may also be written in the form 

g 4- 0-0^2 . . . o„ and 4- 0-a x a 2 . . . a„ 4- -—. 

10" 

If we consider the above process repeated indefinitely, we obtain 

an infinite decimal O-Oja^ . . . , which has the following meaning. 

If we break off this decimal at any place, say the n-th, the point 

P will lie in the interval of length — whose end-points (approxi- 
mating points) are 

g + O-o^ . . . a„ and g + O-o^ . . . a„ + __. 

10 n 



io INTRODUCTION [Chap. 

In particular, the point corresponding to the rational number 
g + O-o^a . . . a n will lie arbitrarily near to the point P if only 
n is large enough; for this reason the points g + 0-a x a 2 . . . a„ 
are called approximating points. We say that the infinite decimal 
g + O-OjOg • • • is the real number corresponding to the point P. 

Here we would emphasize the fundamental assumption that 
we can calculate in the usual way with the real numbers, and 
hence with the decimals. It is possible to prove this using 
only the properties of the integers as a starting-point. But 
this is no light task; and rather than allow it to bar our pro- 
gress at this early stage, we regard the fact that the ordinary 
rules of calculation apply to the real numbers as an axiom, 
on which we shall base the whole differential and integral calculus. 

We here insert a remark concerning the possibility, in certain cases, of 
choosing the interval in two ways in the above scheme of expansion. From 
our construction it follows that the points of division arising in our 
repeated process of subdivision, and such points only, can be represented 
by finite decimals g + Q-a x a % . . . a n . Let us suppose that such a point P 
first appears as a point of division at the ra-th stage of the subdivision. 
Then according to the above process we have chosen at the tt-th stage the 
interval to the right of P. In the following stages we must choose a sub- 
interval of this interval. But such an interval must have P as its left end- 
point. Therefore in all further stages of the subdivision we must choose 
the first sub-interval, which has the number 0. Thus the infinite decimal 
corresponding to P is g + O-ajOj . . . o n 000 .... If, on the other hand, 
we had at the ra-th stage chosen the left-hand interval containing P, then 
in all later stages of subdivision we should have had to choose the sub- 
interval farthest to the right, which has P as its right end-point. Such 
a sub-interval has the number 9. Thus for P we should have obtained a 
decimal expansion in which all the digits from the (n + l)-th onward are 
nines. The double possibility of choice in our construction therefore corre- 
sponds to the fact that for example the number J has the two decimal 
expansions 0-25000 . . . and 0-24999 .... 

3. Expression of Numbers in Scales other than that of 10. 

In our representation of the real numbers we made the 
number 10 play a special part, for each interval was subdivided 
into ten equal parts. The only reason for this is the widespread 
use of the decimal system. We could just as well have taken p 
equal sub-intervals, where p is an arbitrary integer greater 
than 1. We should then have obtained an expression of the 

form g -f- — -| — | + . . . , where each 6 is one of the numbers 
P P z 



I] THE CONTINUUM OF NUMBERS u 

0, 1, . . . , p — 1. Here again we find that the rational numbers, 
and only the rational numbers, have recurring or terminating 
expansions of this kind. For theoretical purposes it is often 
convenient to choose p = 2. We then obtain the binary expan- 
sion of the real numbers, 

*+!+£+..-. 

where each b is either * or 1. 

For numerical calculations it is customary to express the 
whole number g, which for simplicity we here take to be posi- 
tive, in the decimal system, that is, in the form 

a m l(T + a^KT- 1 + ... + a l 10+a v 

where each a„ is one of the digits 0, 1, . . . , 9. Then for 
g + O-a^a ... we write simply 

0-m a m-l ■ • ■ <h a o ' <h a 2 • • • 

Similarly, the positive whole number g can be written in one and 
only one way in the form 

P*P k + /W* _1 + • . . + AjH- &, 

where each of the numbers /?„ is one of the numbers 0, 1 p — 1. 

This, with our previous expression, gives the following result: 
every positive real number can be represented in the form 

fi*P k +P*-iP k - 1 + •■. + PiP+Po+ b - i +k+-.., 

V P 2 

where j8„ and o„ are whole numbers between and p — 1. Thus, 
for example, the binary expansion of the fraction ^ is 

»-lX*+OX2+l + ?+^. 

* Even for numerical calculations the decimal system is not the best. The 
sexagesimal system (p — 60), with which the Babylonians calculated, has the 
advantage that a comparatively large proportion of the rational numbers whose 
decimal expansions do not terminate pobsess terminating sexagesimal ex- 
pansions. 



12 INTRODUCTION [Chap. 

4. Inequalities. 

Calculation with inequalities plays a far larger part in higher 
mathematics than in elementary mathematics. We shall there- 
fore briefly recall some of the simplest rules concerning them. 

If a > 6 and c > d it follows that a + c> b + d, but not 
that a — c> b — d. Moreover, if a > b it follows that ac > be, 
provided c is positive. On multiplication by a negative number 
the sense of the inequality is reversed. If o > b > and 
c > d > 0, it follows that ac > 6d. 

For the absolute values of numbers the following inequalities 
aold: 

\a±b\^\a\ + \b\, |o±6|S=|a|-|*l- 

The square of any real number is greater than or equal to zero. 
Therefore, if x and y are arbitrary real numbers 

(x- yf = x* + y*-2xy^0, 

or 2xy <^ x 2 + y 2 . 

5. Schwarz's Inequality. 

Let a 1} a 2 , . . . , a n and b v b 2 , . . . , b„ be any real numbers. 
In the preceding inequality we make the substitutions * 

Kl y- IM 

for * = 1, *= 2, ...,»= n successively and add the resulting 
inequalities. On the right we obtain the sum 2, for 

/ Kl V. i / Kl V- ) 

W + ... + ".')/ + '"^\V(«i 2 +--- + «»V ' 

/ im y + i ( im Y=i. 

If we divide both sides of the inequality by 2 we obtain 

KM + KM + • • • + KM ^ x 
V(V + • • • + «„ 2 ) V(V + • • • + V) - ' 

* Here and hereafter the symbol Vx, where x > 0, denotes that positive 
Dumber whose square is x. 



I] THE CONTINUUM OF NUMBERS 13 

or finally 

I «A I + I «A I + • • • + 1 a A I ^ V(«i 2 +- • .+a n *W{b* +. . .+6„ 2 ). 

Since the expressions on both sides of this inequality axe positive, 

we may square and then omit the modulus signs: 

(a 1 6 1 + a 2 6 2 + . . . + a n b n f ^ («,»+ . . . +«„*) (V+ ... + 6„ 2 ). 

This is the Cauchy-Schwarz inequah'ty. 

Examples * 

1. Prove that the following numbers are irrational: (a) VS. (b) Vn, 
where n is not a perfect square. (c) -y^3. (d)* x = V2 + aV2 
(e)* *= V3+^2. 

2.* In an ordinary system of rectangular co-ordinates, the points for 
which both co-ordinates are integers are called lattice points. Prove that 
a triangle whose vertices are lattice points cannot be equilateral, 

3. Prove the inequalities: 

(a) * -f i ^ 2, x > 0. (6) x + - g -2, x < 0. 



(«) 



x 



^2, a; =)= 0. 



4. Show that if a > 0, ax 3 + 2bx + ^ f or all values of x if, and only 
ff, J'-acgO. 

5. Prove the following inequalities: 

(a) x 1 + xy + y* ^ 0. 

(6)* a?" + x in -h) -f a^-'V + • . . + y*" ^ 0. 

(c)* x« — 3s» + 4a? — 3a; + 1 ^ 0. 

6. Prove Sohwarz's inequality by considering the expression 

(a lX + bj' + (o 2 x + h)* + . . . + (a n x + &„)«, 
collecting terms and applying Ex. 4. 

7. Show that the equality sign in Sohwarz's inequality holds if, and 
only if, the a's and &'s are proportional; that is, ca v + db v = for all v's, 
where c, d are independent of v and not both zero. 

8. For n = 2, 3, state the geometrical interpretation of Sohwarz's 
inequality. 

9. The numbers Yi> Ys are direction cosines of a line; that is, 
Yi* + Y2 2 = 1. Similarly, tj, 2 + 7] 2 2 = 1. Prove that the equation 
Yj 7 )] + fsVz — 1 implies the equations y, = r) u y t = 7) 2 . 

10.* Prove the inequality 

V / "(»i-&i) i! +-.. +(«„-&„)* =£ VW+--- + V) + aA 6 i* + - •• + &„"> 
and state its geometrical interpretation. 

* The more difficult examples are indicated by an asterisk. 



14 INTRODUCTION [Chap. 

2. The Concept op Function 

1. Examples. 

(a) If an ideal gas is compressed in a vessel by means of a 
piston, the temperature being kept constant, the pressure p 
and the volume v are connected by the relation 

pv = G, 

where C is a constant. This formula, called Boyle's Law, states 
nothing about the quantities v and p themselves, but has the 
following meaning: if p has a definite value, arbitrarily chosen 
in a certain range (the range being determined physically and not 
mathematically), then v can be determined, and conversely: 

C G 

«=-, p=-. 

p v 

We then say that v is a function of p, or in the converse case 
that p is a function of v. 

(b) If we heat a metal rod, which at temperature 0° has length 
l , to the temperature 8°, then its length I will be given, on the 
simplest physical assumptions, by the law 

i=i a + p9), 

where jS, the " coefficient of expansion ", is a constant. Again 
we say that Hb a function of 6. 

(c) In a triangle let the lengths of two sides, say a and b, 
be given. If for the angle y between these two sides we choose 
any arbitrary value less than 180° the triangle is completely 
determined; in particular, the third side c is determined. In 
this case we say that if a and b are given c is a function of the 
angle y. As we know from trigonometry, this function is repre- 
sented by the formula 

c = \/(a* -\-b 2 — 2ab cos y). 

2. Formulation of the Concept of Function. 

In order to give a general definition of the mathematical 
concept of function, we fix upon a definite interval of our number 
scale, say the interval between the numbers a and b, and con- 



I] THE CONCEPT OF FUNCTION" 15 

aider the totality of numbers x which belong to this interval, 
that is, which satisfy the relation 



If we consider the symbol x as denoting at will any of the 
numbers in this interval, we call it a (continuous) variable in the 
interval. 

If now to each value of x in this interval there corresponds 
a single definite value y, where x and y are connected by any 
iaw whatsoever, we say that y is a function of x, and write sym- 
bolically 

y = /(»), V=F{x), y = g(x), 

or some similar expression. We then call x the independent 
variable and y the dependent variable, or we call x the argument 
of the function y. 

It should be remarked that for certain purposes it makes a 
difference whether in the interval from a to 6 we include the 
end-points, as we have done above, or exclude them; in the 
latter case, the variable x is restricted by the inequalities 

« < x < b. 

To avoid misunderstanding we may call the first kind of 
interval (including end-points) a closed interval, the second kind 
an open interval. If only one end-point and not the other is 
included (as for example a<x^b) we speak of an interval 
open at one end (in this case the end a). Finally, we may also 
consider open intervals which extend without bound in one 
direction or both. We then say that the variable x ranges over 
an infinite (open) interval, and write symbolically 

a < a; < 00 or — 00 < x < 6 or — 00 < » < oo . 

In the general definition of a function which is denned in an interval 
nothing is said about the nature of the relation by which the depen- 
dent variable is determined when the independent variable is given. This 
relation may be as complicated as we please, and in theoretical investi- 
gations this wide generality is an advantage. But in applications, and in 
particular in the differential and integral calculus, the functions with 
which we have to deal are not of the widest generality; on the contrary, 
the laws of correspondence by which a value of y is assigned to each x 
are subject to certain simplifying restrictions. 



16 INTRODUCTION [Chap. 

3. Graphical Representation. Continuity. Monotonic Functions. 

Natural restrictions of the general function-concept are 
suggested if we consider the connexion with geometry. The 
fundamental idea of analytical geometry is in fact that of giving 
a curve denned by some geometrical property a characteristic 
analytical representation by regarding one of the rectangular 
co-ordinates, say y, as a function y=f{x) of the other co- 
ordinate x; for example, a parabola is represented by the func- 
tion y = a; 2 , the circle with radius 1 about the origin by the two 
functions y = \/(l — x 2 ) and y = —\/(l — a; 2 ). In the first 
example we may think of the function as defined in the infinite 
interval — oo < x < oo ; in the second we must restrict ourselves 
to the interval — 1 ^ x rgi 1, since 
outside this interval the function has 
no meaning (when x and y are real). 

Conversely, if instead of starting 
with a curve determined geometrically 
, we consider a given function y=f(x), 
we can represent the functional de- 
Fig. a.— Rectangular axn p e ndence of y on a; graphically by 
making use of a rectangular co-ordinate system in the usual 
way (cf. fig. 2). If for each abscissa x we lay off the correspond- 
ing ordinate y=f(x), we obtain the geometrical representation 
of the function. The restriction which we now wish to impose 
on the function-concept is this: the geometrical representation 
of the function shall take the form of a "reasonable" geo- 
metrical curve. This, it is true, implies a vague general 
idea rather than a strict mathematical condition. But we 
shall soon formulate conditions, such as continuity, differentia- 
bility, &c, which will ensure that the graph of a function has 
the character of a curve capable of being visualized geometri- 
cally. At any rate, we shall exclude a function such as the 
following: for every rational value of x, the function y has the 
value 1; for every irrational value of x, the value of y is 0. 
This assigns a definite value of y to each x; but in every 
interval of x, no matter how small, the value of y jumps from 
to 1 and back an infinite number of times. 

Unless the contrary is expressly stated, it will always be 
assumed that the law which assigns a value of the function to 



THE CONCEPT OF FUNCTION 



17 



each value of x assigns just one value of y to each value of x, as 
for example y=x 2 or y = sin a;. If we begin with a curve 
given geometrically it may happen, as in the case of the circle 
x 2 -f y 2 = 1, that the whole course of the curve is not given by 
one single (one-valued) function, but requires several functions — 
in the case of the circle, the two functions y = -\/(l — x 2 ) and 
y = — V(l — x *)- The same is true for the hyperbola 
y2 — x 2 = 1, which is represented by the two functions 
y = <y/(l -\- x 2 ) and y = —- \/{\ + a; 2 ). Such curves therefore 
do not determine the corresponding functions uniquely. Conse- 
quently it is sometimes said that the function corresponding to 





Fig. 3 



Fw. 4 



Multiple-valued functions 



the curve is multiple-valued. The separate functions representing 
the curve are then called the single-valued branches belonging 
to the curve. For the sake of clearness we shall henceforth 
use the word " function " to mean a single-valued function. 
In conformity with this, the symbol \/x (for x S; 0) will always 
denote the non-negative number whose square is x. 

If a curve is the geometrical representation of one function 
it will be cut by any parallel to the y-axis in at most one point, 
since to each point x in the interval of definition there corre- 
sponds just one value of y. Otherwise, as for example in the case 
of the circle which is represented by the two functions 

y=^(l-x 2 ) and y=-V(l-* 2 ), 

such parallels to the y-axis may intersect the curve in more than 
one point. The portions of a curve corresponding to different 
single-valued branches are sometimes so connected with each 

2 (1798) 



i8 



INTRODUCTION 



[Chap. 



other that the complete curve is a single figure which can be 
drawn with one stroke of the pen, e.g. the circle (cf. fig. 3), or, on 
the other hand, the branches may be completely separated, 

e.g. the hyperbola (cf. fig. 4). 

Here follow some further examples 
of the graphical representation of 
functions. 

(a) y = ax. 

y is proportional to x. The graph 
(cf. fig. 5) is a straight line through the 
origin of the co-ordinate system. 

(6) y = ax+ b. 

y is a " linear function " of x. The graph is a straight line through the 
point x = 0, y = b, which, if a #= 0, also passes through the point 
x = — b/a, y = 0, and if a = runs horizontally. 




Fig. 5. — Linear functions 



(C) 



v = - 





i ' 



Fig. 6. — Infinite discontinuities 

y is inversely proportional to a:. If in particular a = 1, so that 

1 

y = -, 

X 

we find, for example, that 

y = 1 for * = 1, y = 2 for x = J, y — J for x = 2. 



I] 



THE CONCEPT OF FUNCTION 



19 



The graph (cf. fig. 6) is a curve, a rectangular hyperbola, symmetrical 
with respect to the bisectors of the angles between the co-ordinate 
axes. 

This last function is obviously not defined for the value x — 0, since 
division by zero has no meaning. The exceptional point x = 0, in whose 
neighbourhood there occur arbitrarily large values of the function, both 
positive and negative, is the simplest example of an infinite discontinuity, 
a subject to which we shall return later (cf. p. 51). 



(d) 



1= 3?. 



As is well known, this function is 
represented by a parabola (cf. fig. 7). 

Similarly, the function y = x* is 
represented by the so-called cubical 
parabola (cf. fig. S). 



V\ 






Fig. 7. — Parabola 




Fig. 8. — Cubical parabola 



The curves just considered and their graphs exhibit a property 
which is of the greatest importance in the discussion of functions, 
namely, the property of continuity. We shall later (§ 8, p. 49) 
analyse this concept in more detail; intuitively it comes to 
this, that a small change in x causes only a small change in y 
and not a sudden jump in its value; that is, the graph is not 
broken off. More exactly, the change in y remains less than any 
arbitrarily chosen positive bound, provided that the change in 
x is correspondingly small. 

A function which for all values of a; in an interval has the 
same value y = a is called a constant; it is graphically repre- 
sented by a horizontal straight line. A function y = f(x) such 
that throughout the interval in which it is defined an increase 
in the value of x always causes an increase in the value of y is 
called a monotonic increasing function; if, on the other hand, 



20 



INTRODUCTION 



[Chap. 



an increase in the value of x always causes a decrease in the 
value of y, the function is called a monotonic decreasing function. 
Such functions are represented graphically by curves which 
in the corresponding interval always rise (from left to right) or 
always fall (cf. fig. 9). 

If the curve represented by y=f(x) is symmetrical with 
respect to the y-axis, that is, if x = —a and x = a give the same 
value for the function, or 

/(-s) =/(*), 

we say that the function is an even function. For example, the 
function y = x 2 is even (cf. fig. 7). If, on the other hand, the 




Fig. 9. — Monotonic functions 

curve is symmetrical with respect to the origin, that is, if 
/(-*) = -f(x), 

we call the function an odd function; for example, the functions 
y = x and y = x 3 (cf. fig. 8) and y=l/x are odd. 



4. Inverse Functions. 

Even in our first example on p. 14 it was made evident that 
a formal relationship between two quantities may be regarded 
in two different ways, since it is possible either to consider the 
first variable as a function of the second or to consider the second 
as a function of the first. If, for example, y = ax -\- b, where 
we assume that a =)= 0, x is represented as a function of y by the 
equation x = (y — b) fa. Again, the functional relationship 
represented by the equation y=x 2 can also be represented by 
the equation x— + \/y, so that the function y = a; 2 amounts 
to the same thing as the two functions x = \/y and * = — y/y. 



THE CONCEPT OF FUNCTION 



21 



Thus, when an arbitrary function y = f(x) is given we can attempt 
to determine x as a function of y, or, as we shall say, to replace 
the function y = f(x) by the inverse function x = <f>(y). 

Geometrically this has the following meaning: we consider 
the curve obtained by reflecting the graph of y=f(x) in the 
line bisecting the angle between the positive ataxia and the 
positive y-axis * (cf. fig. 10). This at once gives us a graphical 
representation of a; as a function of y and thus represents the 
inverse function x = <f>(y). 

These geometrical ideas, however, show us at once that a 



/x-(j>(y) 



y 
y 3 
















j& 






? Z ~ 7 ! 






/ 


/ 1 




y t 


/ 


>- - _ 


/l 1 




/' 







3Cf %2 %3 •% 


/ 












Fig. io. — Inversion of a function 

function y = f(x) defined in an interval has not a single- valued 
inverse function unless certain conditions hold. If the graph of 
the function is cut by a line y = c parallel to the x-axis in more 
than one point, the value y=c will correspond to more than 
one value of x, so that the function cannot have a single-valued 
inverse function. This case cannot occur if y=f(x) is con- 
tinuous and monotonic. For then fig. 10 shows us that to each 
value of y in the interval y^yy z there corresponds just one value of 
x in the interval x&x%, and from the figure we infer that a func- 
tion which is continuous and monotonic in an interval always has 
a single-valued inverse function, and this inverse function is also 
continuous and monotonic. (For a rigorous proof, see p. 67.) 



* Instead of reflecting the graph in this way, we oonld first rotate the co- 
ordinate axes and the curve y — f(x) through a right angle and then reflect 
the graph in the x-axi*. 



22 



INTRODUCTION 



[Chap. 



3. More Detailed Study of the Elementary Functions 

1. The Rational Functions. 

We now pass on to a brief review of the elementary functions 
which the reader has already met with in his previous studies. 
The simplest types of function are obtained by repeated appli- 
cation of the elementary operations: addition, multiplication, 
subtraction. If we apply these operations to an independent 




Fig. ii. — Powere of * 



variable x and any real numbers, we obtain the rational integral 
functions or polynomials: 

y=a -\-a 1 x + . . . + a n x\ 

The polynomials are the simplest and, in a sense, the basic 
functions of analysis. 

If we now form the quotients of such functions, that is, 
expressions of the form 

y _ a o + <h x + • • • + a n x n 
b + \x + . . . + b m x"' 

we obtain the general or fractional rational functions, which are 
defined at all points where the denominator differs from zero. 

The simplest rational integral function is the linear function 
y=ax+b. 



I] THE ELEMENTARY FUNCTIONS 23 

It is represented graphically by a straight line. Every quadratic function 
of the form 

y = ax 2 + bx ■+- C 

is represented by a parabola. The ourves which represent rational integral 
functions of the third degree, 

y = ax 3 + bx 1 + ex + d, 

are occasionally called parabolas of the third order, and so on. 

As examples, we give the graphs of the function y = a;" for the 
indices n = 1, 2, 3, 4 in fig. 11. We see that for even values of n the func- 
tion y=x n satisfies the equation /(— £) = j(x), and is therefore an even 
function, while for odd values of n the function satisfies the condition 
/(—»)= —f(x), and is therefore an odd function. 

The simplest example of a rational function which is not a polynomial 
is the function y = 1/x mentioned on p. 18; its graph is a rectangulaj 
hyperbola. Another is the function y = \jx* (cf. fig. 12). 

2. Algebraic Functions. 

We are at once led away from the domain of rational func- 
tions by the problem of forming their inverses. The most impor- 
tant example of this is the introduction of the function y/x. 
We start with the function y = x", which for x ^ is mono- 
tonic. It therefore has a single-valued inverse, which we denote 
by the symbol *= tyy, or, interchanging the letters used for 
the dependent and independent variables, 

y = y/x = x 1 '". 

In accordance with the definition this root is always non-negative. 
In the case of odd values of n the function x n is monotonic for all 
values of x, including negative values. Consequently for odd 
values of n we can also define y/x uniquely for all values of x; 
in this case \/x is negative for negative values of z. 
More generally we may consider 

y = VR(x), 

where R(x) is a rational function. We arrive at further functions 
of similar type by applying rational operations to one or more 
of these special functions. Thus for example we may form the 
functions 

y=V*+V(* 2 +i), y=a + vV+i). 

These functions are special cases of algebraic functions. (The 
general concept of an algebraic function cannot be denned here; 
see Chapter X.) 



24 



INTRODUCTION 



[Chap. 



3. The Trigonometric Functions. 

While the rational functions and the algebraic functions just 
considered are denned directly in terms of the elementary opera 
tions of calculation, geometry is the source from which we 
first draw our knowledge of the other functions, the so-called 
transcendental functions.* We shall here consider the elementary 
transcendental functions, namely, the trigonometric functions, 
the exponential function, and the logarithm. 

In all higher analytical investigations where angles occur it 
is customary to measure these angles not in degrees, minutes, 

d and seconds, but in radians. 
We place the angle to be 
measured with its vertex at the 
centre of a circle of radius 1, 
and measure the size of the 
angle by the length of the arc 
of the circumference which the 
angle cuts out. Thus an angle 
of 180° is the same as an 
angle of -n radians (has radian 
measure n), an angle of 90° has 
radian measure n/2, an angle 
of 45° has radian measure ir/1, an angle of 360° has radian 
measure 2tt. Conversely, an angle of 1 radian expressed in 
degrees is 

180° 

, or approximately 57° 17' 45". 

■n 

Henceforward, whenever we speak of an angle x, we shall 
mean an angle whose radian measure is x. 

After these preliminary remarks we may briefly remind the 
reader of the meanings of the trigonometric functions sin a;, 
cosa;, tana;, cota;.f These are shown in fig. 13, in which the angle 
x is measured from the arm 00 (of length 1), angles being reckoned 
positive in the counter-clockwise direction. The rectangular 

* The word " transcendental " does not mean anything particularly deep or 
mysterious; it merely suggests the fact that definition of these functions by 
means of the elementary operations of calculations is not possible, " quod 
algebrae vires transcendit ". 

fit is sometimes convenient to introduce the functions secx = 1/cosz, 
cosecj; = 1/sinx. 




Fig. 13. — The trigonometric functions 



I] 



THE ELEMENTARY FUNCTIONS 



25 



co-ordinates of the point A at once give us the functions cos a; 
and sin a;. The graphs of the functions sin as, cos a;, tan a;, cot as 
are given in figs. 14 and 15. 



-ji 




Fig. 14 




Fig. is 



4. The Exponential Function and the Logarithm. 

In addition to the trigonometric functions, the exponential 
function with the positive base a, 

and its inverse, the logarithm to the base a, 

x = lo&y. 

are also regarded as elementary transcendental functions. In 
elementary mathematics it is customary to pass over certain 
inherent difficulties in the definition of these functions, and we 
too shall postpone the exact discussion of the functions until 
we have better methods at our disposal (cf. Chapter III, § 6, 
pp. 167-177, and also p. 191). We can, however, at least 
state the basis of the definitions here. If x = p/q is a 

2* (1798) 



26 INTRODUCTION [Chap. 

rational number (where p and q are positive integers), then — 
the number a being assumed positive — we define a x as 
{/a* = a plq , where the root, according to convention, is to be 
taken as positive. Since the rational values of x are everywhere 
dense, it is natural to extend this function a" so as to make it a 
continuous function denned for irrational values of x also, giving 
values to a x when x is irrational which are continuous with the 
values already defined when x is rational. This gives us a con- 
tinuous function y = a", the " exponential function ", which 
for all rational values of x gives the value of a x found above. 
That this extension is actually possible and can be carried out 
in only one way we meanwhile take for granted; but it must 
be borne in mind that we still have to prove that this is so.* 

The function x = log a y 

can then be defined for y > as the inverse of the exponential 
function. 

Examples 

1. Plot the graph of y = x*. Prom this, without further calculation, 
find the graph of y = -^/x. 

2. Sketch the following graphs, and state whether the functions are 
even or odd: 

(o) y = sin 2*. 
(6) y = 5 cos a:. 

(c) y = sina; + cosar. 

(d) y = 2 sina; + sin2x. 
(c) y = sin(a; + tz). 



(/) y=2coa(x+?). 



(d) V = tan* — x. 
3. Sketch the graphs of the following functions, and state whether the 
functions are (1) monotonic or not, (2) even or odd: 
(a) y = a? (— oo < x < oo ). 
(6) y = a* (0 g a: g 1). 

(c) y=i(-lgigl). 

(d) y=\x\(-l£x£l). 

(e) y= Va?(—1 Sigl). 

\S) y = | * — 1 | (— oo < a; < oo ). 
(?) y = | *» + 4a; + 2 | (-4 S x S 3). 

(A) y = [x] (— oo < x < oo), where [a;] means the greatest integer 
which does not exceed x; that is, [i]^i< [a;] + 1. 

* Cf. pp. 70 and 173. 



I] THE ELEMENTARY FUNCTIONS 27 

(»') y = x — [x] ( — go < x < 00 ). 

0") «/ = Vz— [x] (— 00 < x < 00 ). 

(&) y = x + Vx — [x] ( — 00 < x < 00 ). 

(2) y = I x - 1 1 + I x + 1 1 - 2 (-5 g * g 5). 

(»») y = | a; — 1| — 2 | a; | + | a; + 1 | (— °o < a: < 00). 

Which two of these functions are identical? 

4. A body dropped from rest falls approximately 162* ft. in t see. If 
a ball falls from a window 25 ft. above ground, plot its height above ground 
as a function of t for the first 4 sec. after it starts to fall. 

4. Functions of an Integral Variable. Sequences 
of Numbers 

Hitherto we have considered the independent variable as a 
continuous variable, that is, as varying over a complete interval. 
However, numerous cases occur in mathematics in which a quan- 
tity depends only on an integer, a number n which can take 
the values 1, 2, 3, . . . . Such a function we call a function 
of an integral variable. This idea will most easily be grasped 
by means of examples. 

1. The sum of the first n integers, 

S^n) = 1 + 2+3 + 4+. .. + » = in(n + 1), 

is a function of ». Similarly, the sum of the first n squares, 

S,(n) = 1» + 2 a + 3 2 + . . . + n\ 

is a function * of the integer «. 

* This last sum may easily be represented as a simple rational expression 
in n in the following way. We begin with the formula 

(» + l) 3 - ■/» - 3k 2 + Zv + 1, 

write down this equation for the values » - 0, 1, 2 n, and add. We 

thus obtain 

(n + 1)» - 38, + 3/8, + n + 1; 

on substituting the formula just given for 8 ly this becomes 

38, - (» + l)j(n + l)«-l-|n|-(n+ l){n» + ?n), 

so that 

S, - J»(» + 1) (2» + 1). 

By a similar process the functions 

8,(n) - 1* + 2' + . . . + »», 
S t {n) - 1* + 2* + . . . + B \ 



can be represented as rational functions of n. 



z8 INTRODUCTION [Chap. 

2. Other simple functions of integers are the expression 
n! = 1 . 2 . 3 . . . ra 

and the binomial coefficients 

l)...(n— fc+1) n! 



(n\ n(n • 
k) 



&1 kl(n — k)\ 



for a fixed value of k. 

3. Every whole number n > 1 which is not a prime number is divisible 
by more than two positive integers, while the prime numbers are divisible 
only by themselves and by 1. We can obviously consider the number 
T(n) of divisors of n as a function of the number n itself. For the first 
few numbers this function is given by the following table: 

»=123466789 10 1112 
T(n) =122324243 4 2 6 

4. A function of this type which is of great importance in the theory 
of numbers is ir(n), the number of primes which are less than the number 
n. Its detailed investigation is one of the most interesting and attractive 
problems in the theory of numbers. Here we merely mention 
the principal result of these investigations: the number ■n-(ra) is given 
approximately, for large values of n, by the function * re/log n, where by 
log 7i we mean the logarithm to the " natural base " e, to be denned later 
(pp. 168, 174). 

Functions of an integral variable usually occur in the form 
of so-called sequences of numbers. By a sequence of numbers we 
understand an ordered array of infinitely many numbers a^, a 2 , 
a 3 , . . . , a„, . . . , (not necessarily all different), determined by 
any law whatever. In other words, we are dealing simply with 
a function a of the integral variable n; the only difference is that 
we are using the index notation o„ instead of the symbol a(n). 

Examples 

1. Prove that 1» + 2 s + . . . + r? = (1 + 2 + . . . + n)K 

2. From the formula for 1* + 2 2 + . . . + » s , find a formula for 
l* + 3" + 5* + • • • + (2» + 1) J . 

3. Prove the following properties of the binomial coefficients: 

« G)- C.->** (b) G-i) + 0- (":>">«>• 
< c)1+ (i) + © + - + (»-i) + C)= 2B - 

* That is, the quotient of the number n(n) by the number n/logn differs 
arbitrarily little from 1, provided only that n is large enough. 



I] FUNCTIONS OF AN INTEGRAL VARIABLE 29 

4. Evaluate the following sums: 

(a) 1.2 -f 2.3 + . . . -f- »(» + 1). 



1.2 2.3 m(ra + 1) 



1*.2* 2 2 .3 2 n 2 (» + 1)» 

5. A sequence is called an arithmetic progression of the first order 
if the differences of successive terms are constant. It is called an arith- 
metic progression of the second order if the differences of successive terms 
form an arithmetic progression of the first order; and in general, it is 
called an arithmetic progression of order k if the differences of successive 
terms form an arithmetic progression of order (k — 1). 

The numbers 4, 6, 13, 27, 50, 84 are the first six terms of an arithmetic 
progression. What is its order? What is the eighth term? 

6. Prove that the n-th term of an arithmetic progression of the second 
order can be written in the form an* -f bn -f- c, where a, b, e are inde- 
pendent of n. 

7.* Prove that the »-th term of an arithmetic progression of order k 
can be written in the form an h + ftn* -1 + . . . + pn + q, where 
a,b,...,p,q are independent of n. 

Knd the «-th term of the progression in Ex. 6. 

5. The Concept op the Limit of a Sequence 

The fundamental concept on which the whole of analysis 
ultimately rests is that of the limit, of a sequence. We shall first 
make the position clear by considering some examples. 

n 

We consider the sequence 

1 1 1 

Oj = 1, o, = -, o, = -,... , o„ = 



2 



n 



No number of this sequence is zero; but we see that the larger the number 
n is, the closer to zero is the number a n . If, therefore, we mark off around 
the point an interval as small as we please, then from a definite index 
onward all the numbers a„ will fall in this interval. This state of affairs 
we express by saying that as n increases the numbers a„ tend to 0, or that 
they possess the limit 0, or that the sequence a^, a 2 , a 3 . . . converges to 0. 
If the numbers are represented as points on a line this means that the 
points l/» crowd closer and closer to the point as » increases. 



30 INTRODUCTION [Chap. 

The situation is similar in the case of the sequence 

1 1 1 (-l)"- 1 
o, = 1, a 2 =— -, a s=g. o 4 =—-,..., a„= 

Here, too, the numbers a n tend to zero as n increases; the only difference 
is that the numbers a n are sometimes greater and sometimes less than the 
limit 0; as we say, they oscillate about the limit. 

The convergence of the sequence to is usually expressed 
symbolically by the equation 

lim a„ = 0, 

n — >oo 

or occasionally by the abbreviation 

a„-»-0. 

o n _ 1 . „ _ 1 

*• a 2m — — > a 2m-l — X~, • 

In the preceding examples, the absolute value of the difference be- 
tween a„ and the limit steadily becomes smaller as n increases. This is not 
necessarily the case, as is shown by the sequence 

1,1111 

°i = s» a 2 = 1 ' ° s = 4' a * ~ 2' ° 5 = 6' a " ~ 3' ' " " ' 



that is, in general, for even values n= 2m, a„= a 2m = 1/m, for odd 
values n = 2m — 1, a n = a^ n _ 1 = l/2m. This sequence also has a limit, 
namely, zero; for every interval about the origin, no matter how 
small, will contain all the numbers o B from a certain value of n onward; 
but it is not true that every number lies nearer to the limit zero than the 
preceding one. 

3. a„ 



n + 1 

We consider the sequence 
1 2 

°1 ~ a' a 2 



1_ 2' 2_ 3 "~n+l 

where the integral index n takes all the values 1, 2, 3, . . . . If we write 

a = 1 we see at once that as n increases the number o„ will 

" n+1 

approach closer and closer to the number 1, in the sense that if we mark 
off any interval about the point 1 all the numbers a a following a certain 
a s must fall in that interval. We write 

lim a_ = 1. 



I] LIMIT OF A SEQUENCE 31 

»*- 1 



The sequence 



n % + n + I 



behaves in a similar way. This sequence also tends to a limit as n in- 
creases, to the limit 1, in fact; in symbols, lim a n = 1. We see this 
most readily if we write *->■» 

„ 1 «+2 

n m + n -+• 1 

here we need only show that the numbers r B tend to as n increases. 
Now for all values of n greater than 2 we have n + 2 < 2» and 
n 2 + n + 1 > m 2 . Hence for the remainder r n , we have 

2» 2 

< r « < -2 - - (» > 2 )« 

from which we see at once that r n tends to as n increases. Our discussion 
at the same time gives an estimate of the amount by which the number 
a n (for » > 2) can at most differ from the limit 1; this difference cer- 
tainly cannot exceed 2/n. 

The example just considered illustrates the fact, which we should 
naturally expect, that for large values of n the terms with the highest 
indices in the numerator and denominator of the fraction for a n pre- 
dominate and that they determine the limit. 

4. a n = y£. 

Let p be any fixed positive number. We consider the sequence Oj, o^ 
a s> • • •» o„, . . . , where 

°n = Vp- 

We assert that lim a n = lim -\/p = I. 

n— > 00 n— > «> 

We can prove this very easily by using a lemma which we shall find 
useful for other purposes also. 

If 1 + h is a positive number (that is, if h > —1), and n is an integer 
greater than 1, then 

(1 + h) n > 1 + nh (1) 

Let us suppose that the inequality (1) is already proved for a certain 
value m > 1; we multiply both sides by (1 + h) and obtain 

(1 + h)"* 1 > (1 + mh) (1 + h) = I + (m + l)h + mh». 

If, on the right, we omit the positive term mA 2 the inequality remains 
valid. We thus obtain 

(1 + h)™+ x > 1 + (m + l)h. 

This, however, is our inequality for the index m + 1. It follows therefore 
that if the inequality holds for the index m it holds for the index m + 1 



32 INTRODUCTION [Chap. 

also. Since it holds for m = 2, it holds also for m = 3, hence for m = 4, 
and so on; therefore it holds for every index. This is a simple example 
of a proof by mathematical induction, a type of proof which is often useful. 

Returning to our sequence, we distinguish between the case p > 1 
and the case p < 1 (if p = 1, then \/p is also equal to 1 for every n, 
and our statement becomes trivial). 

If p > 1, then ■yjp will also be greater than 1; we put ^/p = 1 + h n , 
where h n is a positive quantity depending on to, and by the inequality (1) 
we have 

p = (1 + h n )» > 1 + nh n , 

from which it at once follows that 

p— 1 

We therefore see that as n increases the number h n must tend to 0, which 
proves that the numbers a„ converge to the limit 1, as stated. At the 
same time we have a means for estimating how close any o„ is to the limit 1; 
the difference between a„ and 1 is certainly not greater than (p — l)/w. 

If p < 1, then \/p will likewise be less than 1 and therefore may be 
taken equal to 1/(1 + h n ), where h n is a positive number. From this it 
follows, using the inequality (1), that 

_ 1 1 

P ~ (l + h„)" < l + nh n - 

(By making the denominator smaller we increase the fraction.) It follows 
that 

1 + nh n < ~, 

P 

1 / i 

and therefore h. < . 

n 

From this we see that h n tends to as to increases. As the reciprocal 
of a quantity tending to 1, yp itself tends to 1. 

5. a a = a". 

We consider the sequence a n = a", where a is fixed and n runs through 
the sequence of positive integers. 

First, let a be a positive number less than 1. We may then put 
a = 1/(1 + h), where h is positive, and inequality (1) gives 

1 11 

< — -. 



" (1 + h) n 1 + nh nh 

Since the number h, and consequently 1/h, depends only on a, and does 
not change as ra increases, we see that as to increases a™ tends to 0: 

lim a" = (0 < a < 1). 



I] 



LIMIT OF A SEQUENCE 



33 



The same relationship holds when a is zero, or negative but greater than — 1. 
This is immediately obvious, since in any case lim | a | n = 0. 

If a = 1, then a" will obviously be always equal to 1, and we shall 
have to regard the number 1 as the limit of a™. 

If a > 1, we put a = 1 + h, where h is positive, and at once see from 
our inequality that as n increases a" does not tend to any definite limit, 
but increases beyond all bounds. We express this state of affairs by saying 
that a" tends to infinity as n increases, or that a n becomes infinite; in 
symbols, 



lim a" = oo 



(a > 1). 



Nevertheless, as wo must explicitly emphasize, the symbol oo does not 
denote a number with which we can calculate as with any other number; 
equations or statements which express that a quantity is or becomes 
infinite never have the same sense as an equation between definite quanti- 
ties. In spite of this, such modes of expression and the use of the symbol 
oo are extremely convenient, as we shall often see in the following pages. 
If a = — 1, the values of a™ will not tend to any limit, but as n runs 
through the sequence of positive integers it will take the values -f 1 and — 1 
alternately. Similarly, if a < — 1 the value of a" will increase numerically 
beyond all bounds, but its sign will be alternately positive and negative. 



6. Geometrical Illustration of 
the Limits of a" and v"A 
If we consider the ourves y = x" 
and y = x 1 '" = -y/x and restrict 
ourselves for the sake of con- 
venience to non-negative values of 
x, the preceding limits are illus- 
trated by figs. 16 and 17 respec- 
tively. In the case of the curves 
y = x" we see that in the interval 
from to 1 they approach closer 
and oloser to the x-axis as n in- 
creases, while outside that interval 
they climb more and more steeply 
and draw in closer and closer to a 
line parallel to the y-axis. All the 
curves pass through the point with 
co-ordinates x = 1, y = 1 and 
through the origin. 



y 


i r* r* . 

\ti- A 

\\ i /*» 




/ 


o " " I 


'x 



Fig. 16.- 



as n increases 



In the case of the functions y = x 1 '" = + a/x, the curves approach 
closer and closer to the line parallel to the x-axis and at a distance 1 above 
it. On the other hand, all the curves must pass through the origin. Hence 
in the limit the curves approach the broken line consisting of the part of 



34 



INTRODUCTION 



[Chap. 



the y-axis between the points y = and y = 1 and of the parallel to 
the a;-axis y = 1. Moreover, it is clear that the two figures are closely 
related, as one would expect from the fact that the functions y = y /x 
are actually the inverse functions of the ra-th powers, from which we infer 
that each figure is transformed into the other on reflection in the line 
y = «• 



V 






•y «-l2-~ 












/ 







x- 



Fig. 17. — jr 17 " as n increases 



7. The Geometric Series. 

An example of a limit which is more or less familiar from elementary 
mathematics is the geometric series 

1 + g + ?* + . . . + g"- 1 = S n ; 

the number q is called the common ratio of the series. The value of this 
sum may, as is well known, be expressed in the form 



<S« 



1-g" 

l-<7 



provided that q =4= h ^e can derive this expression by multiplying the 
sum 8„ by q and subtracting the equation thus obtained from the original 
equation, or we may verify the formula by division. 

The question now arises, what happens to the sum 8 n when n increases 
indefinitely? The answer is this: the sum iS„ has a definite limit 8 if 
q lies between — 1 and +1, these end values being excluded, and it is 
then true that 

1 



8 



lim S- 



1 



In order to verify this statement we write the numbers 8 n in the form 
1 — q" 1 q" 

— = z . We have already shown that provided 

q 1-g 1-g J r 



S« = 



I] LIMIT OF A SEQUENCE 35 

I g| < 1 the quantity q", and with it — - — , tends to as n increases: 

q 
hence with the above assumption the number 8 n tends, as was stated, 

to the limit as n increases. 

1-? 
_ 1 

The passage to the limit lim(l + g'-(-g»+...-f j"-i) = is 

n—ya 1 — 9 

usually expressed by saying that when | q | < 1 the geometric series can 
be extended to infinity and that the sum of the infinite geometric series 

is the expression . 

1-g 

The sums S n of the finite geometric series are also called the partial 
sums of the infinite geometric series 1 + q + g 2 + . . . . (We must draw 

a sharp distinction between the sequence of numbers S v S s S„, . . . 

and the geometric series.) 

The fact that the partial sums S n of the geometric series tend to the 

limit S = as n increases may also be expressed by saying that the 

infini te geometric series 1 -f q + q* + .. . converges to the sum S = 

when I q | < 1. ! — 9 

8. a a =tyn. 

We shall show that the sequence of numbers 

«i = 1, Oj = V2, a s = {/3 o n = -\/n, . . . 

tends to 1 as n increases, i.e. that 

lim y/n = 1. 

n— *-oo 

Here we make use of a slight artifice. Instead of the sequence a n = \/n 
we first consider the sequence b n = Va n = V-y/i = VVn. When n > 1 
the term b n is also greater than 1. We can therefore put b„ = 1 + h n , 
where h„ is positive and depends on n. By inequality (1), p. 31, we 
therefore have 

Vn = (6„)» = (I + AJ» Sl + ri, 

*w 1 ^Vn-1 Vn 1 

so that h n 5j <J — = -;-. 

n n Vn 

We now have 

1 SS a n = 6„» = 1 + 2A„ + V =£ 1 + J- + -. 

V n n 

The right-hand side of this inequality obviously tends to 1, and therefore 
so does a„. 



n» 



36 INTRODUCTION [Chap. 



9. a„ = Vn + 1 — \/n. 



We assert that lim (Vn + 1 — Vn) == 0. 

To prove this we need only write the expression under discussion in the 
form 



.- , (Vn+l—Vn) (Vn+l+Vn) 

Vn+1— v»= — 



Vn+l + Vft Vn+l + Vn 

we see at once that this expression tends to as n increases. 

10. a„ = — . 
a" 

Let a be a number greater than 1. We assert that as n increases the 

ft 
sequence of numbers a„ = — tends to the limit 0. 

As in the case of \/n above we consider the sequence 

. Vn 

We put V a = 1 + h. Here h > 0, since a and hence V a is greater than 1. 
By inequality (1), p. 31, we have 

vV* = (1 + h) n > 1 + nh, 

Vn _ Vn , Vn 1 



so that Vo_ = 



(1 + h) n — 1 + nh ~~ nh hVn 
1 



Hence a. == --z. 

" nh 1 

Since a n is positive and the right-hand side of this equation tends to 0. 
we see that a_ must also tend to 0. 



Examples 

n s 4- n 1 1 

1. Prove that lim — — = -. Find an N such that for n > N 

„_>.„ 3ft 2 + 1 3 

w 2 I n I J 

the difference between ; and - is (a) less than yo, (6) less than 

l o o o> ( c ) I® 88 than ioooooo- 

2. Find the limits of the following expressions as n -*■ oo : 



I] LIMIT OF A SEQUENCE 37 

(a) W ' +3n+1 . (M n'+Sn+l 
n 8 + 7n» + 2 n« + 7ra» + 2 

( C) 6n« + 2n + 1 g n* + a ^-^ +... + g k 

» 3 + »* 6 »* + M*"" 1 + • • . + &** 

n 

Si" 

3. Prove that lim ^/n* = 1. 

n— >-oo 

4. Prove that lim £- = 0. Find an N such that — < 1 . whenever 

n > N. .->-«2 n 2" 1000 

6. Find numbers N u N& N s such that: 

(a) h < 10 for every " > Nii 

n 1 
(6) 2 s < 100 f ° r 6Very " > N * 

(e) & < Md f0IeYeiyn>N *- 



6. Do the same thing for the sequence a n = Vn +1 — Vn. 

7. Prove that lim ( Vm + 1 — Vn) ( Vn + J) = J. 

8. Prove that lim (v^+1 — v^w) = 0. 

n— >« 

10" 

9. Let a„ = — _. (o) To what limit does o„ converge? (6) Is the 

sequence monotonic? (c) Is it monotonic from a certain n onwards? 
(d) Give an estimate of the difference between a„ and the limit, (e) From 
what value of n onwards is this difference less than jJxf? 

10. Prove that lim — = 0. 

11. Prove that lim ( I + - + . . . + ±\ = I. 

12. Prove that lim (— + + . . . + _L_ ^ = 0. 

.->- W T (n + I)" T ^ (2«)V 

13. Prove that lim (-L- + * + . . . + ^L=\ = 00 . 

»_».„W»i V»+l V2n/ 

H.* Prove that 

«->.i Wn»+ 1 + Vn»+2 ' * ' + Vn 2 + n) = L 
15. Prove that if a and 6^0 are positive, the sequence \/ , a n + 6" 
converges to o. Similarly, for any k fixed positive numbers a : , a 2 , . . . , a 4 
prove that -y^ai* + o s B + . . . + a k n converges, and find its limit. 



38 INTRODUCTION [Chap. 

16. Prove that the Bequenee V2, V2V2, a/2V2\/2 converges. 

Find its limit. 

17.* If v(ra) is the number of distinct prime factors of n, prove that 

lim *0_0l 



6. Fubther Discussion of the Concept oe Limit 

1. First Definition of Convergence. 

From the cases discussed in the last section we are led to 
form the following general concept of limit: 

If an infinite sequence of numbers a^ a 2 , a 3 , . . . , a n , . . . is 
given and if there is a number 1 such that every interval, no matter 
how small, marked off about the point I contains all the points a n 
except for a finite number at most, we say that the number I is the 
limit of the sequence %, a^, . . . , or that the sequence %, &%, . . . 

converges to I; in symbols, lim a„= J. Here we expressly remark 

»—>■«> 
that this includes the trivial case in which all the numbers a n 
are equal to one another and hence also coincide with the limit. 

Instead of the above we may use the following equivalent 
statement: 

If any positive number e be assigned — no matter how small — 
a whole number N = N(e) can be found such that from the index 
N onward (i.e. for n > N(e)) it is always true that | a„ — 1 1 
< e. Of course it is as a rule true that the bound N(e) will 
have to be chosen larger and larger as smaller and smaller 
values of e are chosen; in other words, N(e) will increase 
beyond all bounds as e tends to 0. 

It is important to remember that every convergent sequence 
is bounded; that is, to every sequence a x , a z , a 3 , . . . for which 
a limit I exists there corresponds a positive number M, inde- 
pendent of n, such that for all the terms o„ of the sequence the 
inequality | a„ | < M is valid. 

This theorem readily follows from our definition. We choose 
e equal to 1; then there is an index N such that for n > N it is 
true that \a n — l\ < 1. Amongst the numbers 

I oj — I \, I a 2 - 1 1, . . . , \a s —l\ 
let A be the largest. We can then put M = \ 1 1 -+• A -\- 1 For 



I] FURTHER DISCUSSION OF LIMITS 39 

by the definition of A the inequality | a„ — I | < A -f 1 cer- 
tainly holds for n = 1, 2, . . . , N, while for n > N 

\a n -l\<l^A+l. 

A sequence which does not converge is said to be divergent. 
If as n increases the numbers a„ increase beyond all bounds 
we say that the sequence diverges to + a>, and, as we have 
already done occasionally, we write lim a n = 00. Similarly, we 

write lim a n = — 00 if as n increases the numbers — a n increase 

beyond all bounds in the positive direction. But divergence 
may manifest itself in other ways, as, for example, in the case of 
the sequence ^ = — 1, a 2 = + 1, a 3 = -1, a 4 = +1, .... 
whose terms swing to and fro between two different values* 

In all the examples given above it has happened that 
the limit of the sequence considered is a known number. If 
the concept of limit yielded nothing more than the recognition 
that certain known numbers can be approximated to as closely 
as we like by certain sequences of other known numbers, we 
should have gained very little from it. The fruitfulness of the 
concept of limit in analysis rests essentially on the fact that 
limits of sequences of known numbers provide a means of dealing 
with other numbers which are not directly known or expressible. 

The whole of higher analysis consists of a succession of ex- 
amples of this fact, which will become steadily clearer to us in the 
following chapters. The representation of the irrational numbers 
as limits of rational numbers may be regarded as a first example. 
In this section we shall become acquainted with further ex- 
amples. Before we take up this subject, however, we shaD 
make a few preliminary general remarks. 

2. Second (Intrinsic) Definition of Convergence. 

How can we tell that a given sequence of numbers %, a 2 , 
°s. • • • j «n» • • • converges to a limit, even when we do not know 
beforehand what that limit is? This important question is an- 
swered for us by Cauchy's convergence test.\ 

* Another useful remark: the behaviour of a sequence as regards conver- 
gence is unaltered if we omit a finite number of the terms o». In what follows 
we shall frequently make use of this, speaking of the convergence or divergence 
of series in which the term a, is undefined for a finite number of values of n. 

t Sometimes referred to as the general principle of convergence. 



40 INTRODUCTION [Chap. 

We say that a sequence of numbers a ly a 2 , . . . , a n , . . . is 
intrinsically convergent if to every arbitrarily small positive 
number e there corresponds a number N = N(e), usually de- 
pending on e, such that \ a„ — a m \ < e, provided that n and m 
are both at least equal to N(e). Cauchy's convergence test can 
then be expressed as follows: 

Every intrinsically convergent sequence of numbers possesses 
a limit. 

The importance of Cauchy's test lies in the fact that it allows 
us to speak of the limit of a sequence after considering the se- 
quence itself, without any further information about the limit. 

The converse of Cauchy's test is very easy to prove. For 
if the sequence a v a 2 , ... tends to the limit I, then by the 
definition of convergence we have 

\l — a n | < ^ and | I — a m | < |, 

where e is a positive quantity as small as we please, provided 
only that m and n are both large enough; therefore 

K — a m | = | {I — a m ) — (I — a n ) | ^ 1 1 — a m \ + 1 1 — a„ | <e. 

Since e can be chosen as small as we please, this inequality ex- 
presses our statement. 

Cauchy's test itself becomes intuitively obvious if we think 
of the numbers as represented on the number axis. It then states 
that a sequence certainly has a limit if after a certain point N 
all the terms of the sequence are restricted to an interval 
which can be made arbitrarily small by choosing N large enough. 

In the appendix we shall show how Cauchy's test can be 
proved by purely analytical methods. For the time being we 
accept it as a postulate. 

3. Monotonia Sequences. 

The question whether a given sequence converges to a limit 
is particularly easy to answer when the sequence is a so-called 
monotonic sequence; that is, if either every number of the sequence 
is larger than the preceding number (monotonic increasing se- 
quence) or else every number is smaller than the preceding 
number (monotonic decreasing sequence). We have the following 
theorem: 



I] FURTHER DISCUSSION OF LIMITS 41 

Every monotonia increasing sequence whose terms are bounded 
above {that is, lie below a fixed number) possesses a limit; simi- 
larly, every monotonia decreasing sequence whose terms never fall 
below a certain fixed bound possesses a limit. For the present 
we shall regard these results as obvious, merely referring the 
student to the rigorous proof in the appendix (p. 61). A con- 
vergent monotonic increasing sequence must, of course, tend 
to a limit which is greater than any term of the sequence, while 
in the case of a convergent monotonic decreasing sequence the 
numbers tend to a limit which is smaller than any number of the 
sequence. Thus, for example, the numbers 1/w form a mono- 
tonic decreasing sequence with the limit 0, while the numbers 
1 — 1/w form a monotonic increasing sequence with the limit 1. 

In many cases it is convenient to replace the condition 
that a sequence shall increase monotonically by the weaker 
condition that the terms of the sequence shall never decrease; 
in other words, to allow successive terms of the sequence to 
be equal to one another. We then speak of a monotonic non- 
decreasing sequence, or of a monotonic increasing sequence in the 
wider sense. Our theorem on limits remains true for such 
sequences, and also for sequences which are monotonic non- 
increasing or monotonic decreasing in the wider sense. 

4. Operations with Limits. 

We conclude with a remark concerning calculations with 
limits. From the definition of limit it follows almost at once 
that we can perform the elementary operations of addition, 
multiplication, subtraction, and division according to the follow- 
ing rules: 

If a^, Og, ... is a sequence with the limit a and 6 X , b 2 , . . . is 
a sequence with the limit 6, then the sequence of numbers 
c n = a n + b„ also has a limit, and 

lim c„= a-\- b. 

n— >-«o 

The sequence of numbers c n = a n b„ likewise converges, and 

lim c n = ab. 

Similarly, the sequence c n = a„ — b n converges, and 
lim c_ = a — 6. 



4a INTRODUCTION [Chap. 

Provided the limit b differs from 0, the numbers c„ = — also 
converge, and have the limit " 

lim c„ = * 

R-»-X 

In words: we can interchange the rational operations of calcu- 
lation with the process of forming the limit; that is, we obtain 
the same result whether we first perform a passage to the limit 
and then a rational operation or vice versa. 

For the proof of these simple rules it is sufficient to give one 
example; using this for a model, the reader can establish the 
other statements for himself. We consider e.g. the multipli- 
cation of limits. The relations a n ->a and b„ -> b amount to 
the following: if we choose any positive number e, we need 
only take n greater than N, where N = N(e) is a sufficiently 
large number depending on c, in order to have both 

| a — a n | < e and | b — b„ | < e. 

If we write ah — a n b„ = b(a — a„) + a„(b — b„) and recall that 
there is a positive bound M, independent of n, such that | a„ | <M, 
we obtain 

|«6-o.6.|^|6||a-o.| + |o.||6-6 1 ,|<(|6| + Jf)«. 

Since the quantity ( | b | + M) e can be made arbitrarily small 
by choosing e small enough, we see that the difference between 
ah and a n b n actually becomes as small as we please for all suffi- 
ciently large values of n, which is precisely the statement made 
in the equation 

ah= lim a n b n . 

n—> oo 

By means of these rules many limits oan be evaluated very easily; 
for example, we have 

km — = lun = 1, 

n ra a 

since in the second expression the passages to the limit in numerator and 
denominator can be made directly. 

Another simple and obvious rule is worth stating. IJ 
lim a n = a and lim b n = b, and if in addition a n > b n for every n, 
then a ^ b. However, we are by no means entitled to expect 



I] FURTHER DISCUSSION OF LIMITS 43 

that in general a will be greater than b, as is shown by the 
case of the sequences o n = 1/n, b n = l/2w, for which a = = b 

5. The Number e. 

As a first example of the generation of a number, which can- 
not be stated in advance, as the limit of a sequence of known 
numbers, we consider the sums 

fl - = - 1 + ri + a + - + a- 

We assert that as n increases these numbers S n tend to a definite 

limit ., 

In order to prove the existence of the limit we observe that 
as n increases the numbers S„ increase monotonically. For all 
values of n we also have 1 

1 — - 

2 

The numbers S n therefore have the upper bound 3 and, being 
a monotonic increasing sequence, they possess a limit, which we 
denote by e: 

e = lim S„. 



n- 



Further, we assert that the number e defined as the above 
limit is also the limit of the sequence 



■=K)" 



The proof is simple and at the same time an instructive 
example of operations with limits. According to the binomial 
theorem, which we shall here assume, 



-i+w 1 + n (n-l) 1 j n(n-l)(n-2)..A 1_ 

n 2! n 2 wl n n 

n!\ n) \ n) ' "\ ~ n / 



44 INTRODUCTION [Chap. 

From this we see at once (1) that T n 5S S n , and (2) that the 
T„'s also form a monotonic increasing sequence,* whence the 
existence of the limit lira T n = T follows. In order to prove that 

n — > oo 

T = e, we observe that 

r . >1+1+ i(,_I) + ...+A(,_iY..(i-!=J\ 

2! \ mj n\\ m/ \ m / 

provided that m > n. If we now keep n fixed and let m increase 
beyond all bounds, we obtain on the left the number T and on 
the right the expression S n , so that T 2; S n . We have thus estab- 
lished the relationship T ^ S n 5g T n , for every value of n. We 
can now let n increase, so that T n tends to T; from the double 
inequality it follows that T = lim S n = e. This was the state- 
ment to be proved. «->» 

We shall later (Chapter III, § 6, p. 172) reach this number e 
again from still another point of view. 



6. The Number n as a Limit. 

A limiting process which in essence goes back to classical 
antiquity (Archimedes) is that by which the number it is defined. 
Geometrically tt means the area of the circle of radius 1. We 
therefore accept the existence of this number -n as intuitive, 
regarding it as obvious that this area can be expressed by a 
(rational or irrational) number, which we then simply denote 
by 7T. However, this definition is not of much help to us if we 
wish to calculate the number with any accuracy. We have then 
no choice but to represent the number by means of a limiting 
process, namely, as the limit of a sequence of known and 
easily calculated numbers. Archimedes himself used this process 
in his method of exhaustions, where he steadily approximated 
to the circle by means of regular polygons with an increasing 
number of sides fitting it more and more closely. If we denote 
the area of the regular m-gon (polygon of m sides) inscribed in 

* We obtain T n+ i from T H by replacing the factors 1 — 1/n, 1 — 2/», . . . 

1 2 
by the larger factors 1 — , 1 — , . . . and finally adding a positive 

term. " + x n + 1 



I] FURTHER DISCUSSION OF LIMITS 45 

the circle by/„„ the area of the inscribed 2»i-gon is given by the 
formula (proved by elementary geometry) 

^-sV»-»V'-(£)'- 

We now let m run, not through the sequence of all positive integers, 
but through the sequence of powers of 2, that is, m = 2"; in 
other words, we form those regular polygons whose vertices are 
obtained by repeated bisection of the circumference. The area 
of the circle is then given by the limit 

*r= lim/ 2 .. 

»— >■« 

This representation of tt as a limit actually series as a basis for numeri- 
cal computations; for, starting with the value /„ = 2, we can calculate 
in order the terms of our sequence tending to 77. An estimate of the ac- 
curacy with which any term / a « represents 77 can be obtained by construct- 
ing the lines touching the circle and parallel to the sides of the inscribed 
2"-gon. These lines form a circumscribed polygon similar to the inscribed 

2"-gon, and having dimensions greater in the ratio I : cos — -. Hence 
the area F t * of the circumscribed polygon is given by ^" _1 

Since the area of the circumscribed polygon is evidently greater than that 
of the circle, we have 



1 < n < F.« = 



/. 



2" 



I cos . J 

These are matters with which the reader will be more or less 
familiar. What we wish to point out here is that the calculation 
of areas by means of exhaustion by rectilinear figures whose 
areas can be calculated easily forms the basis for the concept of 
integral, which will be introduced in the next chapter (p. 76). 

Examples 

1.* (a) Replace the statement "the sequence a„ is not absolutely 
bounded" by an equivalent statement not involving any form of the 
words "bounded" or "unbounded". 

(6) Replace the statement "the sequence a n is divergent" by an 
equivalent statement not involving any form of the words " convergent " 
or " divergent ". 



46 INTRODUCTION [Chap. 

2.* Let o t and 6 t be any two positive numbers, and let a t < 6 V Let a, 
and b t be denned by the equations 

aj=Va 1 6„ 6 2 ^ 



Similarly, let a 3 = Va 2 6 2 , 6 3 = 



2 

a 2 + 6 2 



t + K-i 



and in general o„ = Va n _ 1 b n _ 1 , b„ = 

Prove (a) that the sequence a 1? a 2 , . . . , converges, (&) that the sequence 

&j, & 2 converges, (c) that the two sequences have the same limit. 

(This limit is called the arithmetic-geometric mean of Oj and b v ) 

3.* Prove that if lim a n = %, then lim <j„ = £, where a n is the arith- 

metic mean (Oj + o 2 -j- . . . + ««)/»• 

4. If lim a„ = 5, show that the arithmetic means of the arithmetic 

n — >-oo 

means <j„ tend towards £. 

6. Find the error involved in using S„ = 1 + — + • • • + — &s an 

1! re! 

approximation to e. Calculate e accurately to 5 decimal places. 



7. The Concept of Limit where the Variable 
is Continuous 

Hitherto we have considered limits of sequences, that is, of 
functions of an integral variable n. The notion of limit, however, 
frequently occurs in connexion with the concepts of a continuous 
variable x and of a function /(a;). 

We say that the value of the function f(x) tends to a limit 
I as x tends to £, or in symbols 

lim/(z) = I, 

if all values of the function /(a;) for which x lies near enough to 
| differ arbitrarily little from I. Expressed more precisely, the 
condition is as follows: 

// an arbitrarily small positive quantity e is assigned, we can 
mark off about £ an interval | x — £ | < S so small that for every 
point x in this interval different from £ itself the inequality 
| f(x) — / | < e holds. 

Here we expressly exclude the equality of x and £. This is 



Q LIMIT OF A FUNCTION 47 

done purely for reasons of expediency, so as to have the definition 
in a form more convenient for application, e.g. in the case where 
the fnncfaon/(ar) is undefined at the point £, although it is defined 
for all other points in a neighbourhood (p. 159) of £ . 

If our fun ction is defined or considered in a given interval 
only, e.g. Vl - a; 2 in -l^igl, we shall restrict the 
values of x to this interval. Thus if £ denotes an end-point 
of the interval, x is made to approach £ by values on one side 
of £ only (limit from the interior of the interval or one-sided 
limit). 

As an immediate consequence of this definition, we have the 
following fact: if Jim /(*) = I, and ^ x 2 , x & , . . . , x n , . . . is a 

sequence of numbers all different from £ but approaching £ 
as a limit, then lim f(x„) = I. 

ft — >» 

For let e be any positive number; we wish to show that for 
all values of n greater than a certain n the inequality 

!/(*„)- M<« 

holds. By definition, there exists a S > such that whenever 
I x ~ € | < S the inequality 

\f(*)-l\<* 

is true. Since x n -* £, the relation | x n - £\ < S is satisfied 
for all sufficiently large values of n; and for such values it follows 
that \f{x„) — 1 1 < e , as was to be proved. 

We shall now attempt to clarify this abstract definition by means of 
simple examples. Let us first consider the function 



sin a: 
f(x) = , 

x 



defined for x =t= 0. We state that 



.. sins 
km = l. 



We cannot prove this statement simply by carrying out the passage to 
the hmit in numerator and denominator separately, for the numerator 
and denominator vanish when x = 0, and the symbol 0/0 has no meaning. 
We arrive at the proof in the following way. 



4» 



INTRODUCTION 



[Chap. 



From fig. 18 we find by comparing the areas of the triangles OAB and 
OAO and the sector OAB that if < x < n/2 

sin x < x < tan x. 

Prom this it follows that if < | x \ < tt/2, 

x 1 

1 < -r— < • 

sin x cos x 



Hence the quotient lies between the 

x 

numbers 1 and cos x. We know that cos x 

tends to 1 as x -*■ 0, and from this it follows 

that the quotient can differ only arbit- 

x 

rarily little from 1, provided that x is near 

enough to 0. This is exactly what is meant by 

the equation which was to be proved. 




Fig. 1 8 

From the result just proved it follows that 



tan a; ,. sin a; 1 , 

lim = lim lim = 1» 

«— »-o x i_>o x »_>.o cos a; 



and also 



lim 

x— >-0 



= 0. 



This last follows from the formula, valid for < | x | < - , 



1 — cos x (1 — cos x) (1 + cos x) 
x x(\ + cosx) 

sin a; 1 

x ' 1 + cos x 



cos 2 a; 



x(l + cos a;) 



. sinx. 



As x -v the first factor on the right tends to 1, the second to J and the 
third to 0; the product therefore tends to 0, as was stated. 
From the same formula, dividing by x, we obtain 



1 



-c 



sin x\ a 



1 



whence 



lim 



x I 1 + cos x 

1 — cos a; 1 
a? = 2" 



Finally, let us consider the function Vx 2 , defined for all values of x. 
This function is never negative; it is equal to x for x Si and to —a; for 
x < 0. In other words, Vx* = | x\. Consequently the function Vx*/x, 
which is denned for all non-zero values of x, has the value -(-1 when 
x > and — 1 when x < 0. It is therefore impossible for the limit 



I] LIMIT OF A FUNCTION 49 

lim Vx*/x to exist, since arbitrarily near to we can find values of x 

for which the quotient is +1 and other values for which it is — 1. 

In concluding this discussion on limits in connexion with continuous 
variables we remark that it is of course possible to consider limiting pro- 
cesses in which the continuous variable x increases beyond all bounds. 
For example, the meaning of the equation 

i- x *+ 1 r 1 + «* , 
hm -j zr r= hm =1 

"~ x* 
is clear without further discussion. It signifies that the function on the 
left differs arbitrarily little from 1, provided only that x is sufficiently large. 

In these examples we have proceeded as if operations with 
limits obeyed the same laws in the case of continuous variables 
as in the case of sequences. That this is actually true the reader 
can verify for himself; the proofs are essentially the same as for 
limits of sequences. 

Examples 

1. Find the following limits, giving at each step the theorem on limits 
which justifies it: 

(a) lim 3x. (c) lim — — ^-. 

*-^a v ,_».i 2x+2 

(6) lim 4a; + 3. (d) lim V5+f/2xh 

2. Prove that 

. 3"— 1 sin a: , , , ,. sin(r 3 l 
(o) hm = n; (&) lim = 1; (c) lim — ' = 0. 

*— >1 X — 1 *— >-ir 77 — X *— >0 X 

3. Find whether or not the following limits exist, and if they do exist 
find their values: 



Vl — x Vl + x Vl + z-Vl-x 
(a) hm ; (6) hm ; (c) lim ■ , 

*->0 X i_>0 X x->0 X 



8. The Concept of Continuity 
1. Definitions. 

We have already illustrated the notion of continuity in § 2 
(p. 19) by means of examples. Now, with the help of the idea 
of a limit, we are in a position to make the concept of continuity 
precise. 

3 (1798) 



5° 



INTRODUCTION 



[Chap. 



We thought of the graph of a function which is continuous in an 
interval as a curve consisting of one unbroken piece; we also stated 
that the change in the function y must remain arbitrarily small 
provided only that the change of the independent variable x 
is restricted to a sufficiently small interval. This state of 
affairs is usually formulated as follows, with greater prolixity 
but increased precision. A function f(x) is said to be continuous 
at the point £ if it possesses the following property: at the point 
£ the value of the function /(f) is approximated to within an 
arbitrary pre-assigned degree of accuracy e by all functional 

values f(x) for which x is 

f&) +e \ 1 j- yf2^^ near enough to £ . In other 

words, f(x) is continuous 
at £ if for every positive 
number e, no matter how 
small, there can be de- 
termined another positive 
number 8 = 8(e) such 
that |/(*)-/(0|<€ 
(cf. fig. 19) for all points 
x for which | x — £ | < 8. 
Or again: the condition of continuity requires that for the 
point £ the limit equation 

lim /(*)=/(£) 

shall be true. The value of the function at the point £ is the 
same as the limit of the functional values f(x„) for any arbitrary 
sequence x n of numbers converging to £. 

It is important to observe that our condition involves two 
different things: (1) the existence of the limit lim f(x), and 

(2) the coincidence of this limit with /(f), the value of the 
function at the point £ . 

Having now defined continuity of a function /(aj) at a point £ , 
we proceed to state what we mean by the continuity of a 
function f(x) in an interval. This may be defined simply 
in the following way: the function f(x) is continuous in an 
interval if it is continuous at each point of that interval. 
Stated fully, this requires that if a positive number e be 
assigned, then for each point x of the interval there is a 




I] CONTINUITY 51 

positive number 8, depending as a rule on e and on x, such that 
l/(*)-/(*)|<« if |*-*|<8, 

and x lies in the interval a g i g 4. 

Closely related to this is another concept, that of uniform 
continuity. The function f(z) is uniformly continuous in the 
interval a^x<lb if for every positive number e there is a 
corresponding positive number 8 such that for every pair of 
points a^, x 2 in the interval whose distance apart, | cc^ — sc 2 [, is 
less than 8 the inequality l/fo) — f(x 2 ) | < e holds. This differs 
from the definition stated above in that the 8 in the definition 
of uniform continuity does not depend on x, but is equally effec- 
tive for all values of x — hence the name uniform continuity. 

It is quite obvious that a uniformly continuous function is 
necessarily continuous. Conversely, it can be shown that every 
function f(x) which is continuous in a closed interval a ^x^b 
is also uniformly continuous. The proof of this we leave for the 
appendix (p. 64). Even though the reader may not desire to read 
the proof at present he will find it helpful to study the examples 
given at the beginning of Appendix I, § 2, No. 2 (p. 65). But 
until the student has worked through this proof he may assume 
that whenever a function is said to be continuous in a closed 
interval uniform continuity is meant. 

2. Points of Discontinuity. 

We can understand the concept of continuity better if we 
study its opposite, the concept of discontinuity. The simplest 
type of discontinuity occurs at those points at which the function 
makes a jump; that is, at which the function has a definite 
limit as x tends to the point from the right and a definite limit 
as x tends to the point from the left, but these two limits are 
different. Whether or how the function is denned at the point 
of discontinuity itself does not matter. 

For example, the function f(x) defined by the equations 

f(x) = for ** > 1, f(x) = 1 for a" < 1, /(*) = | for x* = 1 

has discontinuities at the points 5=1 and % = — 1. The limits on 
approaching these points from the right and from the left differ by I, and 
the values of the function at these points agree with neither limit, but 
are equal to the arithmetic mean of the two limits. 



5« 



INTRODUCTION 



[Chap. 



It may be noted in passing that our function can be represented, using 
the idea of a limit, by the expression 

f(x)= lim 



1 + x* 



For, if x* < 1, that is, if a; lies in the interval — 1 < x < 1, the numbers 
ie*" will have the limit 0, and the function will have the value 1. If, how- 



Fig. 20 

ever, a; 8 > 1, as n increases a?" will increase beyond all bounds; our function 
will then have the value 0. Finally f or x* = 1, that is, for x = +1 and 
x=—l, the value of the function is plainly J (cf. fig. 20). 

Other curves with jumps are sketched in figs. 21a and 216; they 
represent functions having obvious discontinuities. 

In the case of discontinuities of this kind the limit from the right and 
the limit from the left both exist. We now pass on to the consideration 
of discontinuities in which this is not the case. The most important of 
such discontinuities are the infinite discontinuities or infinities. These 



y\ 




Fig. 2ia 



Fig. 2i* 



are discontinuities such as are exhibited by the functions 1/x or 1/a;* at 
the point 5=0; as x -> 5 the absolute value | f(x) | of the function in- 
creases beyond all bounds. In the case of 1/x the function increases 
numerically beyond all bounds through positive and through nega- 
tive values respectively as x approaches the origin from the right and 
from the left. On the other hand, the function 1/3? has for x = an 
infinite discontinuity at which the value of the function becomes posi- 



CONTINUITY 



53 



tively infinite from both sides (of. fig. 6, p. 18, and fig. 12, p. 22). The 
function y = . . shown in fig. 22, has infinite discontinuities both at 

x = 1 and at x = — 1. 

Finally, we shall illustrate by an example another type of discon- 
tinuity in which no limit from the right or from the left exists. We con- 
sider the function . 

y — sin -, 
x 

defined for all non-zero values of x. This function takes all values 




*2z*h- 




Fig. 22. — Function with infinite 
discontinuities 



Fig. 23. — Oscillating function with 
discontinuity 



between — 1 and +1 when the number 1/x runs through the values from 
(2» — %)tt to (2ra + J) 77, no matter what value the integer n has. At the 
2 

points x = — — — the function will have the value —1, at the points 

(in — l)ir r 



x = - — t-tt— it will have the value +1. From this we see that the func- 
(4n + 1)tt 

tion swings backwards and forwards more and more rapidly between the 

values + 1 and — 1 as x approaches nearer and nearer to the point x = 0, 

and that in the immediate neighbourhood of the point x = an infinite 

number of such oscillations occur (cf. fig. 23). 

It is interesting to observe that in contrast to the above example the 



54 



INTRODUCTION 



fCHAP. 



function «/= xsin l/x (of. fig. 24) remains continuous at the point x= if 
we assign to it the value at that point. This continuity is due to the 
faot that as the origin is approached the factor x damps the oscillations of 
the sine. Yet in the neighbourhood of the origin the function y= x sin l/x 
does not change from monotonic increasing to monotonic decreasing a 
finite number of times. On the contrary, it oscillates backwards and 
forwards an infinite number of times, the magnitude of these oscillations 
becoming as small as we please as the origin is approached. This example 
shows us that even the simple idea of continuity permits of all sorts of 

remarkable possibilities foreign to 
our naive intuitions. 

There is one important fact 
which, must be taken into 
consideration if we are to give 
our ideas greater precision. 
It may happen that at a certain 
point a function is not defined 
by the original law, as for 
example at the point x = in 
the last two examples dis- 
cussed. We have then the right 
to extend the definition of the 
function by assigning to it any 
desired value at such a point. 
In the last example, however, 
we can extend the definition 
in such a way that the function remains continuous at that 
point also, namely, by putting y = when x = 0. This can 
be done whenever the limits from the left and from the right 
both exist and are equal to one another; then we need only 
make the value of the function at the point in question equal to 
these limits in order to make the function continuous there. In 
the case of the function y = sin l/x this is not possible. 

3. Theorems on Continuous Functions. 

In conclusion we quote the following important general 
theorems, whose proofs follow immediately from the remarks on 
operations with limits (p. 41): 

The sum, difference, and product of two continuous functions are 
themselves continuous. The quotient of two continuous functions is 
continuous at every point at which the denominator does not vanish. 




Fig. 24. — Continuous oscillating function 



CONTINUITY 



55 



In particular, it follows that all polynomials and all rational 
functions are continuous except at the points where the denomi- 
nator vanishes. The fact that the other elementary functions, 
such as the trigonometric functions, are continuous will follow 
naturally from later considerations (cf. pp. 69, 97). 



1. Prove that 



2. Prove that 

sin (x — a) 



Examples 

x"sin- 
x 



(a) lim 



X s - 



liiri 

■_>.o sinx 

= 2a'' 



(6) lim 



X + cos * 
x+ 1 



= 1; 



(c) lim cos lfx = 1. 



3. (a) Let /(x) be defined by the equation y = 6x. Find a 8, depend- 
ing on 5, so small that | f(x) — /(5) | < e whenever | x — \ \ < 8, where 

(1) 6 = t>o; (2) e = xfo; (3) e = x^. 

Do the same for (6) f(x) = x* — 2x; 

(c) f(x) = 3** + x 2 - 7; 

(d) f(x) = Vx, * S: 0; 

(e) f(x) = Vx». 

4. (a) Let /(*) = 6* in the interval g x ^ 10. Find a 8 so small 
that | f(x t ) — /(x s ) | < e whenever \x 1 — x t \<B, where (1) t = xfo; 

(2) e is arbitrary, > 0. 

Do the same for (6) f(x) = x« — 2x, — 1 ^ x g 1; 

(c) Jf(a;)=3i 4 + i>-7,2gxg4i 
(rf) /(x) = Vx, ^ x ^ 4; 
(«) f(x) = V**, -2 g x g 2. 



5. Determine which of the following functions are continuous, 
those which are discontinuous, find the points of discontinuity. 



For 



(a) x*sinx. 
(6) a: sin' (a*). 

(c) -sinx. 
x 



(d) 



sinx 
Vz' 



x* + 3x+7 
x 1 — 6x + 8' 
x» + 3a; + 7 
X s — 6x + 9' 
x» + 3a; + 7 
x» — 6x + 10* 
(A) tanx. 



(/) 
(?) 



1 

sinx* 
(j) cotx. 
1 

oosar 
(I) a; cotx. 
(m) (je — x) tanx. 



(») 



(k) 



56 INTRODUCTION [Chap. 

Appendix I to Chapter I 

Preliminary Remarks 

In Greek mathematics we find an extensive working-out of 
the principle that all theorems are to be proved in a logically 
coherent way by reducing them to a system of axioms, as few 
in number as possible and not themselves to be proved. This 
axiomatic method of presentation, which at the same time served 
as a test for the accuracy of the investigation, was at the be- 
ginning of the modern era regarded as a model for other branches 
of knowledge. For example, in philosophy such men as Descartes 
and Spinoza believed that they had made their investigations 
more convincing by presenting them axiomatically, or, as they 
called it, " geometrically ". 

But it was a different matter with modern mathematics, 
which began to develop at about the same time as the new philo- 
sophy. In mathematics the principle of reduction of the material 
to axioms was frequently abandoned. Intuitive evidence in 
each separate case became a favourite method of proof. Even 
in the case of scientists of the first rank we find operations with 
the new concepts based chiefly on a feeling for the right result 
and not always free from mystical associations — particularly 
in the case of the ominous " infinitely small quantities " or 
" infinitesimals ". Blind faith in the omnipotence of the new 
methods carried the investigator away along paths which he 
could never have travelled if subject to the limitations of complete 
rigour. It is no wonder that only the sure instinct of a great 
master could guard agair«t gross errors. 

It is fortunate that this was so, and that the critical counter- 
currents which sprang up in the eighteenth century and rose 
to their full strength in the nineteenth century did not come 
in time to check the development of modern mathematics, but 
only in time to establish and extend its results. But the need 
for critical investigation and consolidation of the advances 
made gradually increased to such an extent that its satisfaction 
is rightly regarded as one of the most important mathematical 
achievements of the nineteenth century. 



I] PRELIMINARY REMARKS 57 

In the differential and integral calculus the critical work of 
Cauchy is particularly important. By formulating the funda- 
mental concepts in a clear and satisfactory way, Cauchy in many 
directions rounded off the work, begun in the eighteenth century, 
of presenting higher analysis in an intelligible manner, free from 
the vagueness due to the use of infinitesimals. 

The principal thing which remained to be done was to re- 
place intuitive considerations in proofs and discussions by con- 
siderations of pure analysis, depending only on numbers and on 
the operations which can be performed with numbers — as we 
say, to " arithmetize " analysis. As a matter of fact, the criti- 
cally-trained mind feels there is something unsatisfactory about 
appeals to intuition in proofs in analysis. We need not go 
into the question of the accuracy or inaccuracy of intuition or 
of the existence of a " pure a priori intuition " in Kant's sense 
in order to recognize that naive intuitive thinking includes much 
vagueness which hinders the approach to completely rigorous proofs 
in analysis. In the following chapters this will strike us more 
and more clearly. Even here we may mention, for example, that 
the concept of a continuous curve is very difficult to grasp in- 
tuitively. A continuous curve need not by any means possess a 
definite direction at every point. In fact, there actually exist 
continuous curves which at no point possess a direction, and 
continuous curves to which no length can be assigned. In 
the face of such facts, even the beginner will admit the need for 
arithmetizing analysis.* 

Yet we must not allow ourselves to forget that a century 
of brilliant and fruitful development of mathematics was possible 
before these requirements were fulfilled. In spite of all its 
defects intuition still remains the most important driving force 
for mathematical discovery, and intuition alone can bridge the 
gap between theory and application. 

We shall now follow Bolzano and Weierstrass in developing 
those lines of thought which yield the rigorous and complete 
proofs of the theorems which we formulated by intuitive means 
in the first chapter. 

* Rigorous mathematical concepts are always very highly idealized forma 
of the ideas which arise intuitively. Hence it is absolutely impossible to dispose 
of problems relating to the ultimate foundations of mathematics by appealing 
to naive intuition. 

S * (1798) 



58 INTRODUCTION [Chap. 



1. The Principle of the Point of Accumulation and its 
Applications 

1. The Principle of the Point of Accumulation. 

In the rigorous discussion of the fundamentals of analysis the 
leading part is played by Weierstrass's principle of the point of 
accumulation. From the intuitive point of view this principle is 
merely the statement of a triviality; but just because it 
summarizes a state of affairs which occurs frequently it is as 
useful as small change is in daily life. The principle is as follows: 

If infinitely many numbers are given in a finite interval, these 
numbers possess at least one point of accumulation; that is, there is 
at least one point £ such that in every interval, no matter how small, 
about the point £ there lie infinitely many of the given numbers. 

In order to prove the principle of the point of accumulation 
arithmetically, we assume to begin with that the given interval is 
the interval from to 1. We now divide this into ten equal parts 
by means of the points 0-1, 0-2, . . . , 0-9. At least one of these 
sub-intervals must contain infinitely many points. Let us sup- 
pose that the interval beginning with the number 0-a 1 is that 
interval (or one of those intervals if there are several). We now 
subdivide this interval into ten parts by means of the points of 
division 0-asjl, 0-a t 2, . . ., Oe^J). Again, it is true that at least one 
of these sub-intervals must contain infinitely many points; let 
it be the sub-interval beginning with the number 0-o x a 2 . We 
again subdivide into ten parts — notice that one of these parts 
must contain infinitely many points — and continue the process. 
We thus arrive at a sequence of digits, a^, a 2 , a a , . . . , each having 
one of the values 0, 1, 2, . . . , 9. We now consider the decimal 

£ = O-a^^dg .... 

It is clear that this is a point of accumulation of our set of num- 
bers. For every interval, no matter how small, in whose interior 
the point £ lies, contains the sub-intervals of our system of sub- 
division from a certain degree of fineness onward, and these 
sub-intervals contain infinitely many numbers of the set. 

If the interval under consideration, instead of being the interval from 
to 1, is, say, the interval from a to a + ft, nothing essential in the above 



I] THE POINT OF ACCUMULATION 59 

argument is changed. The point of accumulation is then represented 
simply by a number of the form 

a + h x O-Oxdja, .... 

2. Limits of Sequences. 

The considerations above throw new light upon the concept 
of the limit of an infinite sequence of numbers a x , a z , a 3 , . . . , 
a„, . . . . We first consider the exceptional case in which 
infinitely many numbers of the sequence are equal to one 
another, and extend our definition by applying the name 
" point of accumulation " to this point (or these points) also. 
If there are infinitely many different numbers in the sequence, 
and if we assume that the numbers a„ of this sequence are 
" bounded ", i.e. that there is a number M such that the in- 
equality I a„ I < M holds for all values of n, the numbers of 
the sequence form an infinite set of numbers in a finite interval, 
since they all lie between — M and M. They must, therefore, 
possess at least one point of accumulation (£). If there is only 
one point of accumulation, it is easy to show that the sequence 
converges, and that its limit is the number g. For let us mark 
off any small interval about the point £. If infinitely many 
points of the sequence were outside this interval, they would 
have a limit point other than g, contrary to hypothesis. Hence 
only a finite number of the numbers of the sequence are exterior 
to the interval, and thus by definition the sequence approaches £ 
If, on the other hand, there are several points of accumulation, the 
sequence approaches no limit. The existence of a limit and the 
uniqueness of the point of accumulation of a bounded sequence 
of numbers are therefore equivalent ideas. 

The case of the non-existence of a limit is to be regarded as the rule 
rather than the exception. For example, the sequence with the terms 
Ojn = 1/n, Ojn-! = 1 — 1/n (» = 1, 2, . . .) has the two points of accumu- 
lation and 1. 

The aggregate of the positive rational numbers may be re- 
garded as a sequence of numbers, in which the ordering by magni- 
tude is, of course, completely destroyed. We arrive most easily 
at such an arrangement in a sequence if we first write down the 
rational numbers as shown on p. 60 and then run through this 
array as shown by the arrows, disregarding those numbers which 



IK! 



60 INTRODUCTION [Chap. 

have already been encountered (such as 2/4). The system of 
rational numbers obviously has all rational and irrational 
points as points of accumulation. It therefore forms a simple 
example of a sequence with an infinite number of points of 
accumulation. 

By means of the concept of convergence we can state the 
principle of the poinb of accumulation in a remarkable form 

which is often convenient 
T~/2 y3~pT /5~T6 /i~*' for applications. 
2/ |/ Z-/ 2./ Z-S 2/ . . From every bounded 

3 y 3_/ 3/3/ 3./ . . infinite set of numbers it 

I /* /^ / * / 5 is possible to choose an 

T {'I s~5 *4 ' ' ' infinite sequence & v a 2 , 

\ ,z j,\ ' a 3> • • • which converges to 

*./*./.. a definite limit $. For 

Enumeration of the rational ttis PU*P<>Se We have 

numbers on ly to take a point of 

accumulation £ of the 
given set of numbers, then to select a number a^ of the set 
whose distance from | is less than 1/10, then a second number 
ffl 2 of the set whose distance from £ is less than 1/100, then a 
third number a 3 whose distance from £ is less than 1/1000, 
and so on. We see at once that this sequence actually con- 
verges to the limit |. 

3. Proof of Cauchy's Convergence Test. 

Let us now return to convergent sequences, i.e. to bounded 
sequences with only one point of accumulation. Cauchy's con- 
vergence test, stated in § 6 (p. 40), now reduces almost to a 
triviality. For let us assume that \a m — a n | is arbitrarily small 
when m and n are sufficiently large. Then the numbers a„ all 
lie in a finite interval, and therefore possess at least one point 
of accumulation f . If now there were a second point of accumu- 
lation 17, the distance of this point from f would be | £ — -q\ = a, 
a positive quantity. Within an arbitrarily small distance from £, 
say within a distance less than a/3 from £, there must be infinitely 
many numbers a„, and hence, in particular, infinitely many 
numbers a„ for which n> N, however large N is chosen. Simi- 
larly, within an arbitrarily small distance from the point 77, say 
within a distance less than a/3 from 17, there are infinitely many 



I] THE POINT OF ACCUMULATION 61 

numbers a m of the sequence; in particular, infinitely many 
numbers a m for which m > N. For these values a„ and a m 
it is true that | a m — a n | > a/3, and this relation is incom- 
patible with the hypothesis that for sufficiently large values 
of N the difference | a„ — a m | is arbitrarily small provided that 
n and m are both greater than N. Consequently there are not 
two distinct points of accumulation, and Cauchy's test is 
proved. 

4. The Existence of Limits of Bounded Monotonic Sequences. 

It is equally easy to see that a bounded monotonic increasing 
or monotonic decreasing sequence of numbers must possess a limit. 
For suppose that the sequence is monotonic increasing, and let 
| be a point of accumulation of the sequence; such a point 
of accumulation must certainly exist. Then £ must be greater 
than any number of the sequence. For if a number a t of the 
sequence were equal to or greater than £, every number a„ 
for which n > I + 1 would satisfy the inequality a„ > o, + " 
> «i sS £. Hence all numbers of the sequence, except the first 
(I + 1) at most, would lie outside the interval of length 
2(a t +i — |) whose mid-point is at the point £. This, however, 
contradicts the assumption that £ is a point of accumulation. 
Hence no numbers of the sequence, and a fortiori no points of 
accumulation, lie above $. So if another point of accumulation 
ij exists we must have -q < £. But if we repeat the above 
argument with ij in place of £ we obtain £ < ij, which is a 
contradiction. Hence only one point of accumulation can exist, 
and the convergence is proved. An argument exactly analogous 
to this of course applies to monotonic decreasing sequences. 

As on p. 41, we can extend our statements about monotonic sequences 
by including the limiting case in which successive numbers of the sequence 
are equal to one another. It is in this case better to speak of monotonic 
non-decreasing and monotonic non-increasing sequences respectively. 
The theorem about the existence of a limi t, remains valid for such 
sequences. 

5. Upper and Lower Points of Accumulation; Upper and Lower 
Bounds of a Set of Numbers. 

In the construction on p. 58 which led us to a point of 
accumulation £ we had at each step to make the choice of a sub- 



6a INTRODUCTION [Chap. 

interval containing infinitely many points of the set. Had we 
always chosen the last sub-interval which contained an infinite 
number of points, we should have been led to a certain definite 
point of accumulation /?. This point of accumulation )8 is called 
the upper point of accumulation or upper limit of the set of num- 
bers, and is designated by the abbreviation lim. It is that point 
of accumulation of the sequence which lies farthest to the right; 
i.e. it is quite possible that an infinite number of points of the 
sequence He above /?, but no matter how small the positive 
number e may be, there are not an infinite number above /? + e. 

If, in the construction on p. 58, we had always chosen the 
first of the intervals containing an infinite number of points of the 
set, we should again have arrived at a certain definite point of 
accumulation a. This point a is called the lower point of 
accumulation or lower limit of the set, and is denoted by lim. 
There may be infinitely many numbers of the set below o, but 
no matter how small the positive number e may be there are 
only a finite number below a — e. The proofs of these facts 
can be left to the reader. 

Neither the upper limit /? nor the lower limit a need belong 
to the set. For example, for the set of numbers a 2n = 1/w, 
a 2n-i = 2 — l/» these limits are respectively a = and )8 = 2, 
but the numbers and 2 do not themselves occur in the set. 

In this example there is no number of the set above /? = 2. 
In this case we say that j8 = 2 is also the upper bound M of the 
set, according to the following definition: M is called the least 
upper bound, or simply the upper bound, of a set of numbers 
if (1) there is no number of the set greater than M, but (2) 
for every positive number e there is a number of the set greater 
than M — e. The upper bound may coincide with the upper 
limit, as the above example shows. But the set a„ = 1 + l/n 
(n = 1, 2, . . .) shows that this is not necessarily the case. Here 
M = 2 and £ = 1. 

Every bounded set of numbers has a least upper bound. For 
let /8 be the upper limit of the set. Either there are no numbers 
of the set greater than /?, or there are such numbers. In the first 
case ft is the least upper bound, since no numbers are above /3 
and there are numbers arbitrarily close to ft below it. In the 
second case let a be a number of the set greater than /?. There 
are only a finite number of numbers of the set equal to or greater 



I] THE POINT OF ACCUMULATION 63 

than a, since otherwise there would be an accumulation point 
above fi, which is impossible. We therefore need only choose 
the greatest of these numbers; it will be the upper bound of 
the set. 

We see that in any case M ^ /}, and we recognize the 
following fact: 

If the upper bound of the set does not coincide with the upper 
limit, it must belong to the set, and is an " isolated " point of the 
set. 

Corresponding statements hold for the lower bound m; it is 
always equal to or less than a, and if m and a do not coincide, m 
belongs to the set and is an isolated point of the set. 

2. Theorems on Continuous Functions 
1. Greatest and Least Values of Continuous Functions. 

A bounded infinite set of numbers must possess a least upper 
bound M and a greatest lower bound m. But, as we have seen, 
these numbers M and m do not necessarily belong to the set; 
as we say, the set does not necessarily have a greatest 01 a 
least value. 

In view of this fact the following theorem on continuous 
functions is by no means so obvious as it appears to simple 
intuition: 

Every function f (x) which is continuous in a closed interval 
a Ss x <: b assumes a greatest value at least once and a least value 
at least once, or, as we say, it possesses a greatest and a least value. 

This may easily be proved in the following way. The values 
assumed by the continuous function f{x) in the interval 
« Sa a <J b form a bounded set of numbers and therefore possess 
a least upper bound M. For otherwise a sequence of numbers 
fi, €2, • • • , f«, ... in our interval would exist for which /(£„) 
increases beyond all bounds. This sequence would have at 
least one point of accumulation £ in the interval. Then arbi- 
trarily near to £ there would always be numbers £„ of our 
sequence for which the expression |/(|j— /(£„) | exceeds 1 
(and in fact is arbitrarily large): that is, the function would be 
discontinuous at the point f Thus a least upper bound M 
exists and hence either there is a point £ such that f(£) = M, 



64 INTRODUCTION [Chap. 

which would prove the statement, or there is a sequence of 
numbers x 1 , x 2 , . . . , x n , . . . in the interval for which 

]imf{x n )=M. 

n— >-oo 

According to the principle of the point of accumulation as formu- 
lated on p. 60 we can select a sub-sequence of the numbers x n , 
which converges to a limit £. Let us call this sub-sequence 
£i» £» •••>&»••• i so that 

lim£ B =£. 

it— >■ 00 

It is then certain that 

lim f(U=M. 

n—¥-<x> 

On the other hand, the function has been assumed continuous 
in the interval, and hence, in particular, at $, so that 

lim f(L) =/(€). 

n— >- oo 

Hence /(£) = M. The value M is therefore assumed by the 
function at a definite point f in the interior or on the boundary 
of the interval, as was stated. An exactly similar discussion 
applies to the least value. 

The theorem about the greatest and least values of con- 
tinuous functions does not remain true in general unless we 
expressly assume the interval to be closed, that is, unless we 
make the hypothesis of continuity refer to the end-points also. 
For example, the function y = 1/x is continuous in the open 
interval 0<sc<oo . It has, however, no greatest value, but 
has arbitrarily large values near x = 0. Similarly, it has no 
least value, but becomes arbitrarily near for sufficiently large 
values of x, without ever assuming the value 0. 

2. The Uniformity of Continuity. 

As we have already seen (cf. p. 54), and as we shall further 
see, the continuity of a function f(x) in a closed interval 
a^x^b leaves room for a variety of possibilities which do 
not suggest themselves intuitively. For this reason we shall 
give logically rigorous proofs of certain consequences of the idea 
of continuity which from a naive point of view se«m quite 



I] CONTINUOUS FUNCTIONS 65 

obvious. The definition of continuity simply states that from the 
relation lim x n = $ the relation lim/(a; n ) =/(f) follows. We 

can also express this in the following way: for each point f 
there corresponds to every e > a number S > such that 
\f( x ) —f(i) I < e whenever | x — £ | < S, provided that all the 
numbers x considered lie in the interval a^x^b. 

For example, in the case of the function y= ex (where c 4= 0) such a 
number S is given by the relation 8 = s/| c (. For the function y = x* we 
can find such a number in the following way. We assume that a = 
and 6=1, and ask ourselves how near to % the number x must lie in order 
that the expression | x 2 — f; 3 j may be less than e. For this purpose we 
write \a?~V\ = \z-Z\\x+f.\^\x-Z\(l+Z). If, therefore, 
we choose 8 ^ e/(l -f 5) we can be sure that | x 1 — ? a | < e. We see in 
this example that the number 8 found in this way depends not only on e, 
but also on the point of the interval at which we are investigating the 
continuity of the function. But if we give up the attempt to make the 
best possible choice of 8 for each |, we can eliminate this dependence of 
8 on 5- For we need only replace % on the right by the number 1, thus 
obtaining for 8 the expression e/2, which is smaller than the previous 
expression for 8 but serves equally well for all points %,. 

The question now arises whether something similar does not 
hold for every function which is continuous in a closed interval. 
That is, we inquire whether it may not be possible to determine 
for each e a 8 = 8(e) depending on e only and not on £, such that 
the inequality 

I /(*)-/(£)!<* 

is true, provided | x — f | < S, for all values of £ at the same 
time (or, better expressed, uniformly with respect to £). As a 
matter of fact, this is possible merely as a consequence of the 
general definition of continuity, without any additional hypo- 
theses. This fact, which first attracted attention late in the 
nineteenth century, is called the theorem of the uniform continuity 
of continuous functions. 

We shall prove the theorem indirectly. That is, we shall 
show that the assumption that a function /(a;) exists which in a 
closed interval a 5S x ^ 6 is continuous and yet not uniformly 
continuous leads us to a contradiction. Uniform continuity 
means that if we wish to make the difference \f(u) —f{v) \ less 
than an arbitrarily chosen positive number e, the numbers w 
and v being chosen in the closed interval a^x^b, we need 



66 INTRODUCTION [Chap. 

only choose u and v near enough to one another, namely, at a 
distance apart less than 8 = 8(e); it is immaterial where in the 
interval the pair of numbers u, v is chosen. Now, if f(x) were not 
uniformly continuous, there would exist a positive (perhaps very 
small) number a with the following property: to every number S n 
of an arbitrary sequence 8 V 8 2 , . . . of positive numbers tending 
to zero there corresponds a pair of values u n , v n of the interval 
for which | «„ — v„ | < 8„ and |/(«„) — f(v n ) | > o. Accord- 
ing to the principle of the point of accumulation the numbers w„ 
must have a point of accumulation f , and so the numbers v n 
must have the same point of accumulation. If we mark off an 
arbitrarily small interval | x — $ | < 8 about this point £, 
an infini t e number of the pairs u„, v n will lie in this interval. 
But this contradicts the assumed continuity of f(x) at the point 
£; for that requires, by Cauchy's convergence test, that for 
points a^ and x 2 near enough to £ 

l/(*i) -/(**) I <«. 

The uniformity of the continuity is thus proved. 

In our proof we have made essential use of the fact that the 
interval is closed.* In fact, the theorem of the uniformity of 
continuity does not hold for intervals which are not closed. 

For example, the function 1/x is continuous in the half -open interval 
< x 52 1, but it is not uniformly continuous. For no matter how small 
the length 8 (< 1) of an interval is chosen, the function will take values 
differing by any fixed number, say 1, in the interval, if only the interval 
lies near enough to the origin, say 8/2 5S a;5S 38/2. The non-uniformity 
of continuity is of course due to the fact that in the closed interval 
<2 x gS 1 the function possesses a discontinuity at the origin. If 
we had considered the example y = x* in the whole (open) interval 
— oo < x < oo instead of in a closed interval, it would not have been 
uniformly continuous. 

3. The Intermediate Value Theorem. 

Another theorem which constantly recurs in analysis is the 
following: 

A function f(x), continuous in a closed interval a ^ x <2 b, 
which is negative for x = a and positive for x = b, (or conversely), 
assumes the value at least once in the interval. 

* Otherwise the point of accumulation \ need not belong to the interval. 



I] CONTINUOUS FUNCTIONS 67 

Geometrically this theorem is trivial, since it merely states 
that a curve which begins below the a;-axis and ends above it 
must cut the axis somewhere in between. Analytically the 
theorem is very easily proved. In the interval there are an 
i nfini te number of points for which f(x) < 0; on account of the 
continuity of the function, in fact, this is true for a whole interval 
beginning at the point a. The set consisting of those points x 
for which f(x) < has a least upper bound g, which is greater 
than a. Since in every neighbourhood of £ there are points x 
for which f(x) < 0, we must have /(f) 5S (whence in particular 
£ 4= b). It is impossible, however, that f(£) < 0, for then f(x) 
would be negative in a sufficiently small neighbourhood of £, 
including values x greater than £ , in contradiction to the hypo- 
thesis that f is the upper bound of the values x for which/(a;) < 0. 
Therefore /(f) = 0, and our assertion is proved. 

A slight generalization of our theorem is: 

If we assume that f(a) = a and f(b) = /}, and if pis any value 
between a and j8, the continuous function f (x) assumes the value p 
at least once in the interval. For the continuous function 

<f> (*)=/(») — f» 

will have different signs at the two ends of the interval, and will 
therefore assume the value somewhere in the interval. 

4. The Inverse of a Continuous Monotonia Function. 

If the continuous function y=f(x) is monotonic in the 
interval a 5S x :£ b, it will assume each value ju. between/(a) and 
/(&) once and only once; hence if y describes the closed interval 
between the values a=/(a) and /}=/(&), to each value of y 
there will correspond exactly one value of x. We can therefore 
think of a; as a single-valued function of y in this interval; that 
is, the function y =f(x) has a unique inverse. We assert that 
this inverse function x = <j>(y) is also a continuous monotonic 
function of y, as y varies within the interval between a and j8. 

The monotonic character of the inverse function x = <f>(y) 
is obvious. In order to prove its continuity we observe that 
from the monotonic character oif(x) it follows that 

l/K)-/(*i)| = hfc-yil>o, 



68 INTRODUCTION [Chap. 

provided that a^ and x 2 are distinct numbers of the interval. 
If A is a positive number less than b — a, the function 

!/(* + *)-/(*) I 

is continuous in the closed interval a^x^b— h. At a point £ 
it therefore has a least value |/(£+ h) — /(£) | = a(h), which 
by our preceding remark is not zero.* From this we conclude that 
if x x and x 2 are two points in the interval for which | a^ — x 2 | ^ h, 
then \f(Xj) — f(x 2 ) | ^ a(h). But this implies the continuity of 
the inverse function. For if | y x — y 2 \ falls below the positive 
number a(h), then we must have | x 1 — x 2 1 < h; and hence if 
a positive number e is given, we need only choose 8 equal to 
a(e) in order to ensure that for all values y for which \y x — y | < 8 
it is also true that | (f>(y x ) — <f>(y) | < e. 

We have therefore established the following theorem: If the 
function y = f (x) is continuous and monotonic m the interval 
a 5j x 5^ b, and f(a) = a, f(b) = /?, then it has a single-valued 
inverse function x = <f>(y), a ^ y ^ /?, and this inverse function 
is also continuous and monotonic. 

5. Farther Theorems on Continuous Functions. 

We leave it to the reader to prove the following almost trivial 
fact: a continuous function of a continuous function is itself 
continuous. That is, if <j>(x) is a function continuous in the interval 
a Sg x ^ b, and its functional values lie in the interval 
a ^ <f>^ /?, and if in addition f(<f>) is a continuous function of 
^ in this last interval, then /(<£(a;)) is a continuous function of 
x in the interval a 5* x ^ b. (Theorem of the continuity of 
functions of continuous functions.) 

It has already been mentioned on p. 54 that the sum, differ- 
ence, and product of continuous functions are themselves continuous, 
and that the quotient of continuous functions is continuous, pro- 
vided that the denominator remains different from zero. 

3. Some Remarks on the Elementary Functions 

In Chapter I we tacitly assumed that the elementary func- 
tions are continuous. The proof of this is very simple. First, 

* On account of the continuity of f(x), a(h) itself of course tends to as A 
does. 



I] THE ELEMENTARY FUNCTIONS 69 

the function f(x) = x is continuous; therefore x 2 = x . x is 
continuous, being the product of two continuous functions, and 
every power of a; is likewise continuous. Thus every polynomial 
is continuous, being the sum of continuous functions. Every 
rational fractional function, being a quotient of continuous 
functions, is likewise continuous in every interval in which the 
denominator does not vanish. 

The function x" is continuous and monotonic. Hence the 
n-th root, being the inverse function of the n-th power, is con- 
tinuous. By the theorem of the continuity of functions of con- 
tinuous functions, the n-th root of a rational function is con- 
tinuous (except where the denominator vanishes). 

The continuity of the trigonometric functions, with which 
the reader is familiar from elementary mathematics, could now 
readily be proved, using the concepts developed above. The 
discussion is not given here, since in Chapter II, § 3 (p. 97), 
this continuity will be seen to follow naturally as a consequence 
of differentiability. 

We shall merely make a few remarks about the definition 
and continuity of the exponential function a x , the general power 
function a;", and the logarithm. We assume, as in § 3, pp. 25-26, 
that a is a positive number, say greater than 1, and if r = pfq 
is a positive rational number (p and q being integers) we take 
a? = a? 1 " as meaning the positive number whose q-th power is 
a". If a is any irrational number and r v r % , . . . , r m , . . . is a 
sequence of rational numbers approaching o, we assert that 
lim a'm exists; we then call this limit a°. 

IB— »-°0 

In order to prove the existence of this limit, by Cauchy's 
test we need only show that | a'» — a r m | is arbitrarily small, 
provided that n and m are sufficiently large. We suppose for 
example that r„ > r ro , i.e. that r n — r m = S, where 8 > 0. Then 

o r » — a r »» = a r >»(a s — 1). 

Since o r "» remains bounded, we need only show that 
I a" - 1 1 = a 8 - 1 

is arbitrarily small when the values of n and m are sufficiently 
large. But 8 is a rational number, and certainly may be made 
as small as we please provided the values of n and m are suffi- 



70 INTRODUCTION [Chap. 

ciently large. Hence if I is an arbitrarily large positive integer, 
8 < l/l if n and m are large enough. Now the relations 
S < l/l and a > 1 give * 

and since a 1 " tends to 1 as I increases (cf. p. 31) our assertion 
follows immediately. 

It may be left to the reader to show that the function a" 
extended to irrational values in this way is also continuous 
everywhere, and, moreover, that it is a monotonic function. For 
negative values of x this function is naturally defined by the 
equation 

. 1 
a" =* — . 

As x runs from — oo to +oo, a" takes all values between and 
+ oo. Consequently it possesses a continuous and monotonic 
inverse function, which we call the logarithm to the base a. In 
like manner we can prove that the general power of is a con- 
tinuous function of x, where a is any fixed rational or irrational 
number and x varies over the interval < x < oo; also that 
sc* is monotonic if a 4= 0. 

The " elementary " discussion of the exponential function, 
the logarithm, and the power a? outlined here will later (Chapter 
HI, § 6, p. 167) be replaced by another discussion which is in 
principle much simpler. 

Examples 

1. Giv« the upper and lower bounds and upper and lower limits for the 
following sequences, and state which belong to the sequence: 

(«) — . n= 1, 2 (5) 0, L_ iL, n = 1, 2, 

»! n! 

n 2n+ 1 n 2n + 1 

(«) —.+ —., m, n= 1, 2, . . . . 
m 3 » a 

* This statement follows from the fact that when a > 1 the power o"* is 
greater than 1 if m/n is positive. This is clearly true. For if o m/ " were less than 
1, then o"* — (o m ' n )" would be a product of n faotors all less than 1, and would 
be less than 1. On the contrary, a" is the product of m faotors all greater than 
1, and so is greater than 1. 



I] THE ELEMENTARY FUNCTIONS 71 

2.* Prove that if f(x) is continuous for a g x g 6, then for every e > 
there exists a polygonal function <p(x) (that is, a continuous function whose 
graph consists of a finite number of rectilinear segments meeting at corners) 
such that I f(x) — <p(x) | < e f or every x in the interval. 

3. Prove that every polygonal function <p{x) can be represented by a 
sum <p(a;) == a + bx + Sc,- 1 x — x t \ , where the x ( '8 are the abscissas of 
the corners. 

Find a formula of this kind for the function /(a;) denned by the equations: 

f(x) = 2i-l(0ga:g2). 
f(x) ~ 5 - x (2 g x S 3). 
f(x) = x — 1 (3 ^ x g 5). 

f(x) = 4(5^^7). 

4. For the following functions f(x) find as in § 1, No. 2, p. 65, a 
8(s) such that \f(xj) — f( Xi ) | < s whenever | x^ — x 2 | < 8(e): 

(a) /(*) = 2* 8 , -1 ^zgl. 

(b) ftx) = x», -a^x^a. 

*(«) A*) = \A = *i -1S«S1. 

6.* The function y= sinl/a has no discontinuities in the interval 

< x < 1. Prove that it is rao< uniformly continuous in that open interval. 

6. A function /(*) is defined for all values of a; in the following manner: 

f(x) = for all irrational values of x; 
Six) = 1/g for rational x = pjq, 

where p/q is a fraction in its lowest terms; (thus for x = ff , f(x) = ^-). 
Prove that /(a;) is continuous for all irrational values of * and dis- 
continuous for all rational values of x. 



Appendix II to Chapter I 

1. Polab Co-ordinates 

In Chapter I we have set the concept of function in the fore- 
ground and have represented functions geometrically by means 
of curves. It is, however, useful to recall * that analytical geo- 
metry follows the reverse procedure, beginning with a curve given 

* See also p. 16. 



72 



INTRODUCTION 



[Chap. 



by some geometrical property and representing this curve by 
a function, for example, by a function which expresses one of the 

co-ordinates of a point of the curve 
in terms of the other co-ordinate. 
This point of view naturally leads 
us to consider, apart from the 
rectangular co-ordinates to which 
we restricted ourselves in Chapter I, 
other systems of co-ordinates which 
may be better suited for the repre- 
sentation of curves given geometri- 
cally. The most important example 
is that of polar co-ordinates r, 8, which are connected with the 
rectangular co-ordinates x, y of a point P by the equations 

x=rcos0, y=rsin0, r 2 =x 2 +y 2 , tan0=^, 



Fig. 25. — Polar co-ordinates 



and whose geometrical interpretation is made clear in fig. 25. 




Fig. 26. — Lemniscate 

Let us consider for example the lemniscate. This is geometrically de- 
fined as the locus of all points P for which the product of the distances 
r t and r 2 from the fixed points F 1 and F t with the rectangular co-ordinates 
x = a, y = and x = —a, y = respectively has the constant value a 2 
(cf. fig. 26). Since 

r,« = (x - a)* + y», r 2 » = (x + a)« + y\ 

a simple calculation gives us the equation of the lemniscate in the form 

(** + y 2 ) 8 - 2a 2 (a* — y 2 ) = 0. 

If we now introduce polar co-ordinates, we obtain 

r* — ZoV^cos'e — sin 2 e) = 0; 



I] POLAR CO-ORDINATES 73 

and if we divide by r a and use a simple trigonometrical formula this 

becomes „ . . „„ 

J- 2 = 2a s cos 20. 

Thus we see that the equation of the lemniscate is simpler in polar co- 
ordinates than in rectangular. 



2. Remarks on Complex Numbers 

Our studies will be based chiefly on the class of real numbers. 
Nevertheless, with a view to the discussions in Chapters VIII, 
IX, and XI we would remind the reader that the problems of 
algebra have led to a still wider extension of the concept of 
number, namely, to the introduction of complex numbers. The 
advance from the natural numbers to the class of all real numbers 
arose from the desire to eliminate exceptional phenomena and 
to make certain operations, such as subtraction, division, and 
correspondence between points and numbers, always possible. 
Similarly, we are compelled, by the requirement that every 
quadratic equation and in fact every algebraic equation shall 
have a solution, to introduce the complex numbers. If, for 
example, we wish the equation 

x 2 + 1 = 

to have roots, we are obliged to introduce new symbols i and — i 
as the roots of this equation. (As is shown in algebra, this is 
sufficient to ensure that every algebraic equation shall have a 
solution.*) 

If a and b are ordinary real numbers, the complex number 
c= a-\- ib denotes a pair of numbers (a, b), calculations with 
such pairs of numbers being performed according to the follow- 
ing general rule: we add, multiply, and divide complex numbers 
(among which the real numbers are included as the special case 
b = 0), treating the symbol i as an undetermined quantity, and 
then simplify all expressions by using the equation i 2 = — 1 to 
remove all powers of i higher than the first, thus leaving only an 
expression of the form a -f- ib. 

We may assume that the reader already has a certain degree 
of familiarity with these complex numbers. We shall neverthe- 

* That every algebraic equation possesses real or complex roots is the 
statement of the " fundamental theorem " of algebra. 



74 INTRODUCTION [Chap. 

less emphasize a particularly important relationship which we 
shall explain in connexion with the geometrical or trigonometrical 
representation of the complex numbers. If c = x -f- iy is such 
a number, we represent it in a rectangular co-ordinate system 
by the point P with co-ordinates x and y. By means of the equa- 
tions x = r cos 6, y= r sin 0, we now introduce the polar co- 
ordinates r and (cf. p. 72) instead of the rectangular co-ordinates 
x and y. Then r 2 = Va^ + y 2 is the distance of the point P from 
the origin, and is the angle between the positive a;-axis and 
the segment OP. The complex number c is now represented in 
the form 

c = r(cos0 + t sin0). 

The angle is called the amplitude of the complex number c, 
the quantity r its absolute value or modulus, for which we also 
write \c\. To the "conjugate" complex number o = x — iy 
there obviously corresponds the same absolute value, but (except 
in the case of negative real values of c) the angle — 0. Clearly 

r* = | c | 2 = cc = a 2 + f. 

If we use this trigonometrical representation the multipli- 
cation of complex numbers takes a particularly simple form. 
For then 

c.c' = r(cos0 + t sin0) . r'(cos0' + i sin0') 
== ri (cos 8 cos 8' — sin 8 sin 8') 

+ i (cos 8 sin 8' -f sin 8 cos #'). 

If we recall the addition theorems for the trigonometric functions 
this becomes 

c.c' = rr'(cos(0 + 0') + i sin(0 + 0') ). 

We therefore multiply complex numbers by multiplying their 
absolute values and adding their amplitudes. The remarkable 
formula 

(cos + i sin 0) (cos 0' + % sin $') = cos (0 + 0') + i sin (0 + 0') 

is usually called De Moivre's theorem. It leads us at once to the 
relation 

(cos + » sin0) n = cosn0 + t sinw0, 



I] COMPLEX NUMBERS 75 

which e.g. at once enables us to solve the equation x n = 1 for 
positive integers n, the roots (the so-called roots of unity) being 

«i = « = cos h"in — , e 2 = e 2 = cos \~ % sin — , . . ., 

n n n n 

n-l (n— 1)7T . . . (w— 1)tt „ , 

«„_! = e« l = cos 5 i 1- 1 sin^ '— , e„ = c" = 1. 

Moreover, if we imagine the expression on the left-hand 
side of the equation (cos0 + isaxd) n = cosn0+ isaxnd ex- 
panded by the binomial theorem, we need only separate real 
and imaginary parts in order to obtain expressions for cos«0 
and sinn0 in terms of powers and products of powers of sin0 
and cos0. 

Examples 

1. Plot the graphs of the following functions: 

r = sin 9. r = eos 5<p. 

r=f. 1 

„• a r — — ; ;> * constant. 

r = sin 69. cos (9 — a) 

2. Find the polar equation of 

(a) the circle of radios a with its centre at the origin; 
(6) the circle of radius a with centre (a, 9 ); 
(c) the general straight line. 

3. Use De Moivre's theorem to express cos 29 and sin 29 in terms of 
sin 9 and 00s 9. Similarly, for cos 39, sin 39, cos 59, sin 59. 

Prove that cos»9 is a polynomial in cos 6, and also that if n is odd 
sin »6 is a polynomial in sin 9. 

4. Work out the following expressions, and state the modulus and 
amplitude of each of the numbers involved and of the answers: 

(a) -3.2*. (f)i 11 *. 

(6) (4 + 4t)(i - i V3»). (g) (1 -f- if. 

(c) (1 + i)(l - t). (A) (3 - 3») 2/ ». 

(d) (V3 - »•)«. (fc) li/». 

(e) l 1/a . (/) (16*) 1 ". 

5.* Prove that if s = cos — + » sin — , where n is an integer Greater 
than 1, n n "* K«»rer 

e r _|_ 6 ai- _l e s>- _l # # _ 1 s ny = /0 if m is not a factor of v, 

\n if n is a factor of v. 



CHAPTER II 

The Fundamental Ideas of the Integral 
and Differential Calculus 

Among the limiting processes of analysis there are two 
which play an especially important part, not only because they 
arise in many different connexions, but chiefly because of the 
very close reciprocal relation between them. Isolated examples 
of these two limiting processes, differentiation and integration, 
were considered even in classical times; but it is the 
recognition of their complementary nature and the resulting 
development of a new and methodical mathematical procedure 
that marks the beginning of the real systematic differential and 
integral calculus. The credit of initiating this development 
belongs equally to the two great geniuses of the seventeenth 
century, Newton and Leibnitz, who, as we know to-day, made 
their discoveries independently of one another. While Newton 
in his investigations may have succeeded in stating his concepts 
more clearly, Leibnitz's notation and methods of calculation are 
more highly developed; even to-day these formal portions of 
Leibnitz's work form an indispensable element in the theory. 

1. The Definite Integral 

We first encounter the integral in the problem of measuring the 
area of a plane region bounded by curved lines. More refined 
considerations then permit us to separate the notion of integral 
from the naive intuitive idea of area, and to express it analyti- 
cally in terms of the notion of number only. This analytical 
definition of the integral we shall find to be of great significance, 
not only because it alone enables us to attain complete clarity 



Chap. II] 



THE DEFINITE INTEGRAL 



77 



in our concepts, but also because its applications extend far 
beyond the calculation of areas. 

We begin by considering the matter intuitively. 

1. The Integral as an Area. 

Let us suppose that we are given a function f(x) which is 
continuous and positive in an interval, and that a and b (a<b) 
are two values in that interval. We think of the function as re- 
presented by a curve, and consider the area of the region which 
is bounded above by the curve, at the sides by the straight lines 
x = a and x = b, and below by the portion of the ataxia be- 
tween the points a and b (fig. 1). 

That there is a definite meaning in speaking of the area 
of this region is an assumption inspired by intuition, which we 





Fig. i 



a, b ~x 

Fig. a. — Upper sum and lower sum 



here state expressly as a hypothesis. We call this area F a *> the 
definite integral of the function i(x) between the limits a and b. 
When we actually seek to assign a numerical value to this area, 
we find that we are in general unable to measure areas with 
curved boundaries; but we can measure polygons with straight 
sides by dividing them into rectangles and triangles. Such a 
subdivision of our area is usually impossible. It is, however, 
only a short step to conceive of the area as the limiting value 
of a sum of areas of rectangles, in the following manner. We 
subdivide the part of the z-axis between a and b into n equal 
parts, and at each point of division we erect the ordinate up to 
the curve; the area is thus divided into n strips. We can no 
more calculate the area of such strips than we could that of the 
original surface; but if, as shown in fig. 2, we find first the least 
and then the greatest value of the function f(x) in each sub- 
interval, and then replace the corresponding strip (1) by a rectangle 



7« FUNDAMENTAL IDEAS [Chap. 

whose height is equal to the least value of the function, and (2) 
by a rectangle whose height is equal to the greatest value of the 
function, we obtain two step-shaped figures. (In fig. 2 the first 
of these is drawn with a solid line, the second being shown by 
dotted lines.) The first step-shaped figure obviously has an 
area which is at most equal to the area F a b which we are trying 
to determine; the second has an area which is at least as large as 
F a ". If we denote the sum of the areas of the first set of rect- 
angles by F n (lower sum), and the sum of the areas of the 
second set by F n (upper sum), we have the relation 

F\^ F a "^T n . 

If we now make the subdivision finer and finer, i.e. let n 
increase without limit, intuition tells us that the quantities 
F n and F„ approach closer and closer to each other and tend 
to the same limit F a b . We may therefore consider our integral 
as the limiting value 

F a " = Km F n = lim T„. 



n " 



Intuition also shows us the possibility of an immediate 
generalization. It is by no means necessary that the n sub- 
intervals should all be of the same length. They may, on the 
contrary, have different lengths, provided only that as w increases 
the length of the longest sub-interval tends to 0. 

2. The Analytical Definition of the Integral. 

In the above section we have considered the definite integral 
as a number given by an area, and hence to a certain extent 
pieviously known, and have subsequently represented it as a 
limiting value. We shall now reverse the procedure. We no 
longer take the point of view that we know by intuition how an 
area can be assigned to the region under a continuous curve, 
or, indeed, that this is possible; we shall, on the contrary, begin 
with sums formed in a purely analytical way, like the upper 
and lower sums defined previously, and shall then prove that 
these sums tend to a definite limit. We take this limiting value 
as the definition of the integral and of the area. We are naturally 
led to adopt the formal symbols which have been used in the 
integral calculus since Leibnitz's time. 



n] 



THE DEFINITE INTEGRAL 



79 



ke* f( x ) De a function which is positive and continuous in 
the interval agigi (of length b — a). We think of the in- 
terval as divided by (n — 1) points x 1 , x 2 , . . . , x n _ ± into » equal 
or unequal sub-intervals, and in addition we put x = a, x n = b. 
In each interval we choose a perfectly arbitrary point, which 
may be within the interval or at either end; suppose that in the 
first interval we choose the point fj, in the second the point 
£ 2 , • • • > in the n-th the point £„. Instead of the continuous 
function f(x) we now consider a discontinuous function (step- 
function) which has the constant value /(&) in the first sub- 
interval, the constant value /(f 2 ) in the second sub-interval, . . . , 




Fig. 3. — To illustrate the analytical definition of integral 

the constant value /(£„) in the n-th sub-interval. As is shown in 
fig. 3, the graph of this step-function defines a series of rectangles, 
the sum of whose areas is given by the expression 

F n = (x, - *„)/(&) + (x 2 - *,)/(£,) +... + («.- *„-!)/(£„). 

This expression is usually shortened by using the summation 
sign 2: 

*■„=£(*„-*„_!)/(£); 

K-l 

by introducing the symbol 

Aa;,, = x v — x r _ t 
we can abbreviate it still further: 



v-l 



80 FUNDAMENTAL IDEAS [Chap. 

(Here the symbol A is not a factor, but denotes " difference ". 
The whole inseparable symbol Ax„, by definition, means the 
length of the y-th sub-interval.) Our basic assertion may now 
be stated as follows: 

If we let the number of points of division increase without limit 
and at the same time let the length of the longest sub-interval tend 
to 0, then the above sum tends to a limit. This limit is independent 
of the particular manner in which the points of division x 1; x 2 , . . . , 
x n _ 1 and the intermediate points £ v £ 2 , . ■ . , £„ are chosen. 

This limiting value we shall call the definite integral of the 
function/(a:), the integrand, between the limits a and b; as we have 
already mentioned, we shall consider it as the definition * of the 
area under the curve y=f{x), for a^x^b. Our basic 
assertion may then be re-worded thus: If f(x) is continuous 
in a ^ x ^ b its definite integral between the limits a and b exists. 

This theorem on the existence of the definite integral of a 
continuous function can be proved by purely analytical methods, 
without appealing to intuition. We shall nevertheless pass it 
over for the present and return to it in the Appendix to this 
chapter (p. 131), after the use of the concept of integral has 
stimulated the reader's interest in constructing a firm foundation 
for it. For the moment we shall content ourselves with the fact 
that the intuitive considerations on pp. 77-78 have made the 
theorem appear extremely plausible. 

3. Extensions, Notation, Fundamental Rules. 

The above definition of the integral as the limit of a sum led 
Leibnitz to express the integral by the following symbol: 

£f(x)dx. 

The integral sign is a modification of a summation sign which 
had the shape of a long S. The passage to the limit from a sub- 
division of the interval into finite portions Ax v is suggested by 
the use of the letter d in place of A. We must, however, guard 
ourselves against thinking of dx as an " infinitely small quan- 
tity " or " infinitesimal ", or of the integral as the " sum of 

* Of course we may also define the notion of area in a purely geometrical 
way, and then prove that snch a definition is equivalent to the above limit- 
definition (ci. Chap. V, § 2, No. 1 (p. 268) ). 



II] 



THE DEFINITE INTEGRAL 



81 



& 







Fig. 4 



an infinite number of infinitely small quantities ". Such a con- 
ception would be devoid of any clear meaning; it is only a naive 
befogging of what we have previously carried out with precision. 

In the above figures we have assumed (1) that the function 
f(x) is positive throughout the interval, and (2) that b > a. The 
formula which defines the integral as the limit of a sum is, how- 
ever, independent of any such assumptions. For if f(x) is negative 
in all or part of our interval, the only effect is to make the corre- 
sponding factors /(£,) in our sum negative instead of positive. 
To the region bounded by the part of the curve below the a;-axis 
we shall naturally assign a negative area, which is in agreement 
with the familiar convention of sign in analytical geometry. 
The total area bounded by a 
curve will thus in general be the 
sum of positive and negative 
terms, corresponding respectively 
to the portions of the curve above 
and below the as-axis.* 

If we also omit the condition 
a < b and assume that a > 6, 
we can still retain our arithmetical 
definition of integral; the only change is that when we traverse 
the interval from a to b the differences Ax p are negative. We 
are thus led to the relation 

£f(x)dx=—£f(x)dx, 

which holds for all values of a and b (a =)= b). In conformity with 
this we define / f(x)dx as equal to zero. 

Our definition immediately gives the basic relation (see fig. 4): 

fj(x)dx + f b f(x)dx = fj{x)dx 

for a < b < c. By means of the preceding relations we at 
once find that this equation is also true for any position of the 
points a, b, c relative to one another. 

We obtain a simple but important fundamental rule by 

• For the area of regions bounded by arbitrary closed curves see Chap. V, 
§ 2, p. 269. 

4 (1708) 



8» FUNDAMENTAL IDEAS [Chap. 

considering the function cf(x), where c is a constant. From 
the definition of the integral we immediately obtain 

J cf(x) dx — c J f(x) dx. 

Further, we assert the following addition rule: If 

then 

j^f(x)dx — J <f>(x)dx + J tfi(x)dx. 
The proof is quite simple. 

We add a final remark, which is perfectly obvious, but very important 
in applications, about the " variable of integration ". We have written 

our integral in the form / f(x)dx. For evaluating the integral it does not 

•'a 

matter whether we use the letter x or any other letter to denote the 
abscissae of the co-ordinate system, i.e. the independent variable. The 
particular symbol we use for the variable of integration is therefore a matter 

of complete indifference; instead of / f(x)dx we could equally well write 
pb pb J a 

I f(t)dt or / f(u)du or any similar expression. 

2. Examples 

We are now in a position to carry out the limiting process 
prescribed by our definition of the integral, and thus actually 
to calculate the area in question in a number of special cases; this 
we shall do in a series of examples, where (except in No. 5, p. 86) 
we shall make use of the upper or lower sum alone.* 

1. Integration of a Linear Function. 

We first consider the function f(x) = x", where n is an integer greater 
than or equal to 0. For n = 0, i.e. for f(x) = 1, the result is so obvious 
that we simply write it down: 



rldx— I dx= b — a. 



For the function f(x) = x the integration is again a triviality from the 
geometrical point of view. The integral of the function f(x) = x. 



£ 



xdx, 

* We leave it as a useful exeroise for the reader to prove that in the follow- 
ing examples we actually do arrive at the same result, whether we use the 
upper sum or the lower. 



m 



EXAMPLES OF INTEGRATION 



83 



is simply the area of the trapezoid shown in fig. 6, which by an elemen- 
tary formula has the value 

J(6-o)(6 + a)=i(6 s -o»). 

We shall now verify that our limiting process leads to exactly the same 
result. In calculating the limit we can restriot ourselves to the discussion 
of upper sums or lower sums. We subdivide the interval from a to 6 into 
n equal parts by means of the points of division 

a + h, a + 2h, . . . , a + (» — l)h, 

where h — (6 — a)/n. The integral must then be the limit of the foDow- 
ing sum, which is an upper sum if 6 < a and a lower sum if 6 > a: 

h{a + (a + h) + (a + 2h) + . . . + (a + n— lh)} 
= h{na + h + Zh + . . . + (m - l)h}. 





^> 



Fig. 6 

By an elementary formula we have 

1 + 2 +... + (»_ l) = in(n - 1), 
and our expression may therefore be written in the form 

As n increases the right-hand side obviously tends to the limit 

(6 -a){a+ i(b - a)} = J(6 2 - a"), 
which was to be proved. 

2. Integration of jc 2 . 

A problem not quite so simple is that of integrating the function 
f(x) = a; 2 , or, in geometrical language, of determining the area of the region 
bounded by a segment of a parabola, a segment of the x-axis and two 
ordinates. We consider e.g. the integral 



•'n 



3? dx, 
where 6^0 (see fig. 6), and divide the interval ^ x ^ 6 into » equal 



84 FUNDAMENTAL IDEAS [Chap. 

parts of length h = b/n; the area which we wish to find is then the limit 
of the following expression (upper sum): 

h(h* + 2W + 3% 2 + • • • + » 2 A 2 ) = A 3 (l 2 + 2 2 + . . . + »») 
= fc^l 2 + 2 2 + . . . + n 2 )/» 3 . 

The sum enclosed in brackets, however, has already been found (see 
p. 27, footnote): 

1» + 2* + • • • + » 2 = in(n + 1) (2ra + 1). 

If we substitute this expression and rewrite the result in a slightly 
different form, our sum becomes 

6 s i 



!('+D(*+D- 



As n increases beyond all bounds this tends to the limit ^6 3 , and we obtain 
the required integral formula 



•'n 



x 2 dx = i& 3 . 

From this, using the general relationships given above, we immediately 
derive the general formula 

fx* dx = \x*dx- fx* dx = %(b* - a 3 ). 

J a Ja •'0 



3. Integration of x a , where a is any Positive Integer. 

As a third example we consider the integration of the function 
V = /(*) = * a . 

where a is any positive integer. For the computation of the integral 

■b 
xPdx 



"a 



(where we assume < a < b) it would be inconvenient to divide the 
interval into n equal parts.* The passage to the limit may, however, be 
accomplished very easily if we effect a subdivision in " geometric pro- 
gression " in the following manner. We put \/b\a = q and subdivide the 
interval by the points 

a, aq, aq\ .a, ag"" 1 , ag" = 6. 

* We should then be obliged to base the evaluation of the integral upon the 
calculation of the limit of — L^ (l a + 2 a + . . . + n a ) as n -»■ °o ; the reader 
may work this out for himself as indicated in the footnote on d. 27. 



II] EXAMPLES OF INTEGRATION 85 

The required integral is then the limit of the following sum: 

a« (aq-a)+ (aqf (ag 2 - aq) + (aq*) a (a« 3 - og 2 ) + . . . 
+ (tup- 1 )* (aq n — aq"- 1 ) 

= «+l(g_l){l-)- 3 a+l_j_ 3 2(a+l)_^_ g 3(a+l)+ . . . + 3 (n-l)(a+l) }, 

The terms in the last bracket form a geometric progression with com- 
mon ratio q a+1 4= 1. If we sum this progression, we obtain for the whole 
expression the value 

"" +1 (g-D g ga+1 _ I • 

We now replace q by its value (b/a) 1 !"; our sum then takes the form 

q-l 



(6«+l _ n «+l) 



S*+i— 1* 



If we now let n increase without limit, the first factor retains its value. 
Since q 4= 1 we can use the formula for the sum of a geometric progression 
and write the second factor in the form 



r + r- 1 + • ■ ■ + I' 



and as the equation q = (b/a) 1 !" shows that q tends to 1 as » -> 00 , the 
second factor will have the limit l/(a + 1). Thus finally the value of our 
integral is given by the formula 



"a 



xP-dx— (6*+ 1 — a a+1 ). 

a -f- 1 



The above calculation is simple in principle, but somewhat compli- 
cated in detail. We shall later find that it can be entirely avoided, once 
we are better acquainted with integration theory. 

4. Integration of x a , where a is any Rational Number other than — 1. 

The result obtained above may be generalized considerably without 
essentially complicating the method. Let a = r/« be a positive rational 
number, r and s being positive integers; then in the evaluation of the 
integral given above nothing is changed except the evaluation of the limit 

-^rj as q approaches 1. This expression is now simply . T_ ., . 

Let us put q 1 !* = t (t 4= 1): then as q tends to 1, t will also tend 

f» 1 

to 1. We have therefore to find the limiting value of as t 

T r+ * — 1 

approaches 1. If we divide both numerator and denominator by t — 1 
and transform them as before the limit simply becomes 

T"- 1 + f-» + • • • + 1 

hm ; — ; ; . 

- — - +1 



8< 5 FUNDAMENTAL IDEAS [Chap. 

Since both numerator and denominator are continuous in t this limit is 
at once determined if we substitute t = 1. We thus arrive at the limit 

s 1 

~, — = — r^i ; anc * so f° r every positive rational value of a we obtain 

the integral formula 



•J a 



x"dx = (b a + 1 — a a + 1 ). 

oc -f- 1 



This formula remains valid for negative rational values of a, provided 
we exclude the value a = — 1 for which the formula used above for the 
sum of the geometric progression loses its meaning. We have now to 

investigate the limit of the expression — vr , for negative values of a, 

say a = —r/s. To do this we put q~ x l' = t; we obtain 

q = t - *, q a+1 = g-fr— «)/» = T r_ ». 

We accordingly seek to determine the limiting value of 

t-« — 1 _ 1 — t* 

T r-« _ i _ T r _ T »* 

We leave it to the reader to prove that this limit is again equal to 
— —— ; that is, that we have the integral formula 



* a 



x°-dx = (6 a + 1 — o a+1 ) 

a+ 1 

for the general case of rational values of a either positive or negative, 
with the exception of a = — 1. 

The form of the right-hand side of this equation shows that the ex- 
pression is not valid for a = — 1, since both numerator and denominator 
would then be zero. 

It is natural to suppose that the range of validity of our last formula 
extends also to irrational values of a. We shall aotually establish this in 
§ 7 (p. 129) by a simple passage to the limit. 

5. Integration of sin a; and cos a;. 

As a last example we consider the function f(x) = sin as. This too we 
shall treat by means of a special device. We express the integral 



J a 



saxxdx 
i 

as the limit of the following sum: 

8 h = *{sin(a + h) + sin(a + 2h) + . . . + sin(a -f nh)}, 

where h = . We multiply the right-hand bracket by 2 sin _, and 



II] EXAMPLES OF INTEGRATION 87 

recall the well-known trigonometrical formula 

2 sinu sine = cos(u — ») — cos(« + v); 

provided h is not a multiple of 2n, we thus obtain the formula 

A_ j cos ( a + - J — cos ( a + - h J + cos f a + - h J — cos (a + - h J 



*»- 



2 sin - 



h [ / , h\ I , 2n 4- 1 



2 sin- 



(.+»)-„(. + t+i»)j. 



2 

Since a + «* = 6, the integral becomes the limit of 
A 



Jcos(a+*)-cos(6 + *)| M *^0. 



2 sin- 
2 

Now we know from Chapter I (p. 47) that as h tends to 0, the expres- 
sion r/sin- approaches the limit I. The desired limit is then simply 
00s a — cos 6, and we thus arrive at the integral formula 

sinx dx = — (cosi — cos a). 



r- 



In the same way, as the reader m*y verify for himself, we obtain the 
formula 



•'o 



cosx dx = sin 6 — sin a. 
a 

Almost every one of these examples has been attacked by means of 
some special method or particular device. The essential point of the 
systematic integral and differential calculus is the very fact that instead 
of such special devices we utilize considerations of a general character 
which lead us directly to the desired result. In order to arrive at these 
methods we must now turn our attention to the other fundamental con- 
cept of higher analysis, the derivative. 



Examples 

1. Find the area bounded by the parabola y = 2a? + x + 1, the 
ordinates « — 1 and x= 3, and the z-axis. 

2. Find the area bounded by the parabola y = %x* -+- 1 and the straight 
line y = 3 + x. 



88 FUNDAMENTAL IDEAS [Chap. 

3. Find the area bounded by the parabola y 2 = 5x and the straight 
line y = 1 + x. 

4. Find the area bounded by the parabola y = x 2 and the straight 
line y = ax + 6. 

5. Using the methods in the text, evaluate the integrals 

rb rb rb 

(a) I (x + l) a dx, (6) j sinax&e, (c) f co&axdx, 
Ja Ja Ja 

where a is an arbitrary integer. 

6. Use the formulae obtained in Ex. 5, along with the identities 
sin 2 * = I — b cos 2b, cos 2 x = J + £ cos 2*, to prove that 

r b „ , b — a , sin26 — sin2a 

/ COS Z XdX= ;;— + 

Ja 



rb 

I sva i xdx = 

Ja 



2 4 

6 — a sin26 — sin2a 



7. By use of Ex. 1, p. 28, evaluate / x*dx, using division into equal 

J a 

-intervals. 

8. Evaluate / (1 — x) n dx (where n is an integer) by expanding the 



sub-intervals, 



bracket. 



3. The Derivative 

The concept of the derivative, like that of the integral, is of 
intuitive origin. Its sources are (1) the problem of constructing 
the tangent to a given curve at a given point and (2) the problem 
of finding a precise definition for the velocity in an arbitrary 
motion. 

1. The Derivative and the Tangent. 

We shall first take up the tangent problem. If P is a point 
on a given curve (see fig. 7), we shall, in conformity with naive 
intuition, define the tangent to the curve at the point P by means 
of the following geometrical limiting process. In addition to the 
point P, we consider a second point P x on the curve. Through 
the two points P, P x we draw a straight line, a secant of the 
curve. If we now let the point P ± move along the curve towards 
the point P, this secant will tend to a limiting position which is 
independent of the side from which P 1 approaches P. This 



II] 



THE DERIVATIVE 



89 



limiting position of the secant is the tangent, and the statement 
that such a limiting position of the secant exists is equivalent 
to the assumption that the curve has a definite tangent or a 
definite direction at the point P. (We have used the word " as- 
sumption " because we have actually made one. The hypothesis 
that the tangent exists is valid for most simple curves, but is by 
no means true for all curves, or even for all continuous curves.) 
Once we have represented our curve by means of a function 
y=f(%) the problem arises of representing our geometrical 
limiting process analytically, 
using the function f(x). We 
take the angle which a straight 
line I makes with the sc-axis as 
being the angle through which 
the positive a>axis must be 
turned in the positive direction* 
in order to become for the first 
time parallel to the line I. Let 
% be the angle which the 
secant PP X forms with the 
positive x-axis (cf. fig. 7) and a the angle which the tangent 
forms with the positive aj-axis. Then if we disregard the case of 
a perpendicular tangent we obviously have 

lim cij = a, 

where the meaning of the symbols is perfectly clear. If x, y(=f(x)) 
and a^, 2/i(=/( a; i)) are the co-ordinates of the points P and P 2 
respectively, we immediately havef 

_ vi — y _ /fa) —/(*) . 

9 

and thus our limiting process is represented by the equation 

1- /fa)-/(z) X 

lim J -±-±± — ±±-! = tan a. 





6* 


■^y-f(x) 


p/a 


■^\<ti 




¥ 



Fig. 7. — Chord and Tangent 



tan aj : 



*i" 



X, 



X 



* That is, in such a direction that a rotation of ir/2 brings it into coincidence 
with the positive y-axis; in other words, counter-clockwise. 

t In order that this equation may have a meaning, we must assume that 
< I x — x y I < 8, 8 being chosen sufficiently small. In what follows, corre- 
sponding assumptions will often be made tacitly in the steps leading up to 
limiting processes. 



90 FUNDAMENTAL IDEAS [Chap. 

The expression 

/fo)— /(») ^ th — V = ty 
a^ — x Xy — x Ax 

we call the difference quotient of the function y = f(x), since the 
symbols Ay and Aa; denote the differences of the function 
y=f(x) and of the independent variable x. (Here, as on p. 79, 
the symbol A is an abbreviation for difference, and is not a factor.) 
The tangent of a, the direction angle of the curve,* is therefore 
equal to the limit to which the difference quotient of our function 
tends when a^ tends to x. 

We call this limit the derivative \ of the function y=f(x) 
at the point x and, as Lagrange did, use the symbol y' =/'(#) to 

denote it, or, as Leibnitz did, the symbol t -^ or -^i-J or — f(x). 

dx dx dx 

On p. 100 we shall discuss the meaning of Leibnitz's notation in 

more detail; here we would point out that the notation f'(x) 

expresses the fact that the derivative is itself a function of x, 

since it has a definite value for each value of a; in the interval 

which we are considering. This fact is sometimes emphasized by 

the use of the terms derived function, derived curve (see p. 99). 

We again quote the definition of the derivative: 

*i — ► * X-y — x 
or 

f=& =f{x)= lj m /(*l)-/W = Um ^ 

dx dx *,->* x^ — x a*-=>-oAa; 

- lim /(»+*)-/(*) > 
*->o h 

where in the last expression we have replaced Xj by x + h. 

It is impossible to find the derivative merely by putting 
a^ = x in the expression for the difference quotient, for then the 
numerator and denominator would both be equal to and we 

* The slope or gradient of the curve is given by tana, and hence the term 
gradient is occasionally used for the derivative of the function represented by 
the curve. 

t The term differential coefficient is also used, particularly in the older text- 
books. 

J Cauchy's notation Df(x) is also occasionally found in the literature. 



II] THE DERIVATIVE 91 

should be led to the meaningless expression 0/0. On the con- 
trary, the actual performance of the passage to the limit in each 
individual case depends upon certain preliminary steps (trans- 
formation of the difference qaotient). 

For example, for the function f(x) = x s we have * 

J^-f- X. 

X^ — X Xy — X 

This function x 1 + x is not the same function as Xl ~ — , for the function 

Kj — x 

x t + x is defined at one point where the quotient Xl ~ x is undefined, 

x 1 — x 
namely, the point x 1 = x. For all other values of x 1 the two functions 
are equal to one another; hence in the above passage to the limit, in 
which we specifically required that x, =|= x, we obtain the same value 

for lim as for lim fe + x). But since the function x 1 + x is de- 

*,-».* X 1 — X x l -)-x 

fined and continuous at the point x 1 = x,we can do with it what we could 
not do with the quotient, namely, pass to the limit by simply putting x 1 = x. 
For the derivative we then obtain the expression 

ax 

The carrying out of such a process, i.e. the actual formation of 
the derivative, is called the differentiation of the function f(x). 
We shall see later how this process of differentiation can 
actually be carried out in all important cases. 

Now the fact that the problem of differentiating a given 
function has a definite meaning apart from the geometrical 
intuition of the tangent is of great significance. The reader 
will recall that in the case of the integral we freed ourselves 
from the geometrical intuition of area, and on the contrary based 
the notion of area on the definition of the integral. Now, inde- 
pendently of the geometrical representation of a function 
V=f( x ) by means of a curve, we shall define the derivative of 
the function y =f(x) as being the new function y' —f'(x) given 
by the equation above, provided always that the limit of the 
difference quotient exists. If this limit exists we say that the 
function f(x) is differentiable. From now on we shall assume that 
every function dealt with is differentiable unless specific men- 

* Cf. p. 89, second footnote. 



02 



.FUNDAMENTAL IDEAS 



[Chap. 



fcion is made to the contrary.* It should be observed that if the 
function f(x) is to be differentiable at the point x the limit as 

h -> of the quotient l~ must exist independently 

of the manner in which h tends to 0, whether it be through positive 
values or through negative values or without restriction as to 
sign. 

Once we have found the derivative/'^), we take the direction 
which makes an angle a with the positive a-axis given by the 
equation tana =f'(x) as the direction of the tangent to the 
curve at the point (x, y). We thus avoid the difficulties which 
arise out of the indefiniteness of the geometrical view, since we 








^ 



Fig. 8. — Tangents to graphs of increasing and decreasing functions 

base the geometrical definition on the analytical and not vice 
versa. 

Nevertheless, the visualization of the derivative as the tangent 
to the curve is an important aid to understanding, even in purely 
analytical discussions. Accordingly we shall at once accept the 
following statement based on geometrical intuition: 

If f'(x) is positive and the curve is traversed in the direction of 

increasing x, then the tangent slants upwards, and therefore at the 

point in question the curve rises as x increases; if, on the other hand, 

f'(x) is negative, the tangent slants downwards and the curve falls 

as x increases (see fig. 8). Analytically this follows from the 

fix -\- h) fix) 

remark that the limit of ' ^— cannot be positive 

unless the function is increasing at the point x, by which we 

* Examples of cases In which this assumption is not satisfied will be given 
later (see p. 97). 



n J THE DERIVATIVE 93 

mean that for all values of h sufficiently close to the value of 
f(x + h) is greater or smaller than/(x) according as h is positive 
or negative. We can, of course, make a corresponding statement 
for the case where f'(x) is negative. 

2. The Derivative as a Velocity. 

Just as naive intuition led us to the notion of the direction 
of the tangent to a curve, so it causes us to assign a velocity to a 
motion. The definition of velocity leads us once again to exactly 
the same limiting process as we have already called differentia- 
tion. 

Let us consider, for example, the motion of a point on a 
straight line, the position of the point being determined by a 
single co-ordinate y. This co-ordinate y is the distance, with its 
proper sign, of our moving point from a fixed point on the line. 
The motion is given if we know y as a function of the time t, 
y =f(t). If this function is a linear function f(t) = ct -f b, we call 
the motion a uniform motion with the velocity c, and for every pair 
of values t and ^ which are not equal to one another we can write 

„- /fc)-/(Q 
h-t 

The velocity is therefore the difference quotient of the function 
ct+b, and this difference quotient is completely independent 
of the particular pair of instants which we fix upon. But what 
are we to understand by the velocity of motion at an instant t 
if the motion is no longer uniform? 

In order to arrive at this definition we consider the difference 
quotient ■'MizM, wn ich we shall call the average velocity in 

the time interval between ^ and t. If now this average velocity 
tends to a definite limit when we let the instant ^ come closer 
and closer to t, we shall naturally define this limit as the velocity 
at the time *. In other words: the velocity at the time t is the deri- 
vative 

«,-»-« ty t 

From this new meaning of the derivative, which in itself has 
nothing to do with the tangent problem, we see that it really is 



94 FUNDAMENTAL IDEAS [Chap. 

appropriate to define the limiting process of differentiation as a 
purely analytical operation independent of geometrical intuitions. 
Here again the differentiability of the position-function is an 
assumption which we shall always tacitly make, and which, in 
fact, is absolutely necessary if the notion of velocity is to have 
any meaning. 

As a simple example of the connexion between motion and velocity 
we consider the case of a freely falling body. We begin with the experi- 
mentally established law that the distance traversed in time t by a freely 
falling body is proportional to t 3 , and therefore can be represented by a 
function of the form 

V = /(«) = «*. 

As on p. 91, we find immediately that the velocity is given by the ex- 
pression /'(<) = 2at, which shows us that the velocity of a freely falling 
body increases in proportion to the time. 

3. Examples. 

We now proceed to work out a number of examples of the actual dif- 
ferentiation of functions. We begin with the function y — f(x) = c, where 
c is a constant. It is then always true that f(x + A) — f(x) = c — c = 0, 

fix + h) — fix) 

so that lira — - = 0; that is, the derivative of a constant is zero. 

h— >o A 

For a linear function y = f(x) = ex -f- b, we find that 

Further, we shall differentiate the function 

y = /(*) = »". 

at first assuming that a is a positive integer. Provided x l =t= x, we have 
/(*i) ~ /(*) = *i a ~ *' . 

X 1 — X X l — X ' 

the right-hand side of this equation is equal to as," -1 + a^ a- *a; -{-••• + x a ~ 1 , 
as we see either by direct division or by using the formula for the sum of 
a geometric progression. The new expression for the right-hand side of 
the equation is a continuous function, and so we can carry out the passage 
to the limit (x 1 — ¥■ x) by simply replacing x 1 everywhere by x. Each term 
is then a;" -1 , and since the number of terms is exactly a, we obtain 



II] THE DERIVATIVE 



95 



We arrive at the same result if a is a negative integer — 0; we must, 
however, assume that x is not zero. We then find that 



/to)- 

*1- 


-/(*) 

- X 


1 1 

x l — X 


aP— xf 

X — Xj 

- 2 *i + ... 


1 

' a^a;^ 






x^xfi 





Once again we can cany out the passage to the limit simply by replacing 
x-, everywhere by x. Then just as above we obtain for the limit the 
expression 

Hence for negative integral values of a the derivative is again given by 

/ = ax*- 1 . 

Finally, we shall prove the same formula where * is positive and a. any 
rational number. We suppose that a. = p/q, where p and q are both in- 
tegers and, moreover, positive. (If one of them were negative no essential 
changes in the proof would be needed; for a = the result is already 
known, since x" is then constant.) We now have 

/to) ~ /(*) _ «!** - x*H 

X 1 — X X 1 — X 

If we now put x 11 ' = I and * 1 1 '» = 5 lf we obtain 

/to) -/(«) = 5i»- V> = 51*-* + ^p-'g+.-.-f gp-i 
*i-* 5i«-5« 5i 0_1 + 5i*- a ^ + . - - + 5*- 1 * 

After this last transformation we can immediately perform the passage 
to the limit (x t -> x or, what amounts to the same thing, §, -> §), and thus 
obtain for the limiting value the expression 



or finally 



? 5*" 3 2 ? 



which is formally the same result as before. We leave it for the reader to 
prove for himself that the same differentiation formula holds for negative 
rational indices also. We shall come back (p. 130) to the differentiation of 
powers once we have developed the theory in a more connected form. 
As a further example we finally consider the differentiation of the 



96 FUNDAMENTAL IDEAS [Chap. 

trigonometric functions, sina; and cosa:. We use the elementary trigono- 
metrical formula 

ain(a: + a) — sina ; sina; cosh + cosa; sink — sina; 

h h 

cosa — 1 , sinA 

= sina; 1- cosa; . 

A A 

Now from Chapter I, § 7 (pp. 47-48), we know that 

,. sinA , ,. cosh — 1 
hm — — = 1, lim = 0. 

»— >-0 A 4— >0 A 

For the required derivative we thus immediately obtain 

, dlsinx) 

y = — ^ - = cosx. 

dx 

The function y = cosa: can be differentiated in exactly the same way. 
Starting with 

cos(a; -f A) — cosa; cosa — 1 . sinA 
: — — — = cosa; sina; , 



and taking the limit as a -*■ 0, we at once obtain the derivative 

, d(cosa;) 

y = — ' = —sina;. 

dx 

4. Some Fundamental Rules for Differentiation. 

Just as in the case of the integral, certain simple but funda- 
mental rules for forming the derivative follow immediately from 
the definition. If (f> (x)=f(x) + g(x), then <f>' {x) =- /' (x) -)- g' '(x); 
again, if ip(x) = cf(x) (where c is a constant), then ifi'(x) = cf (x). 
For we have 

<j>(x+h)-<f>(x) = f(x+h)-f(x) g(x +h)-g(x) 
h h ^ h 

and 

^x+JQ-tix) _ J(x+h)-f(x) 
h ° h ' 

and our statements follow directly by passage to the limit. 

According to these rules, for example, the derivative of the 
function <f>(x) =f(x) -f ox -f b (where a and b are constants) is 
given by the equation 

f(s) =/'(*) + a. 



II] 



THE DERIVATIVE 



97 




5. Differentiability and Continuity of Functions. 

It is useful to note that if we know that a function can 
be differentiated we need not give any special proof of its 
continuity. 

If a function is differentiable, then it is necessarily continuous. 

For if the difference quotient -^^ ~^~ '~J^ X ' approaches a 

h 

definite limit as h tends to zero, the numerator of the fraction, 
that is, f(x + h) — f(x), must tend to zero with h; and this fact 
expresses the continuity of 
the function f(x) at the 
point x. 

The converse of this, 
however, is absolutely false; 
it is not true that every con- 
tinuous function has a de- 
rivative at every point. The 
simplest example disprov- 
ing this assumption is the 
function /(x) = | x \, i.e. f{x) ^—xioxx-g.0 and f{x) = x for 
x ^ 0; its graph is shown in fig. 9. At the point x = this 
function is continuous, but has no derivative. The limit of 

f(x -\- h) fix) 

7 — — is equal to 1 if A tends to through positive 

values, and is equal to —1 if A tends to zero through negative 
values; if we do not restrict the sign of ft, no limit exists. We 
say that our function has different right-hand and left-hand 
derivatives at the point x, where by right-hand derivative and 
left-hand derivative we mean respectively the limiting values of 
f(x+h)—f(x) , , „ , 
y as ft approaches through positive values only 

and negative values only. The differentiability of a function thus 
requires not merely that the right-hand and left-hand derivatives 
exist, but that they are equal. Geometrically the inequality 
of the two derivatives means that the curve has a sharp 
corner. 

As further examples of points where a continuous function is 
not differentiable we consider the points where the derivative 
becomes infinite, i.e. the points at which there exists neither a 



9 8 



FUNDAMENTAL IDEAS 



[Chap. 



right-hand nor a left-hand derivative, the difference quotient 

j — ^-^ increasing beyond all bounds as h -*■ 0. For 

h 

example, the function y = f(x) = \/x = x* is denned and con- 
tinuous for all values of x. For all non-zero values of x its deri- 
vative is given (p. 95) by the formula y 1 = 5 ar*. At the point 

x = we have • * - — j — ^— - = — = A - *, and we see at once 
h A 

that as h -»■ the expression has no limiting value, but, on the 
contrary, tends to oo. This state of affairs is often briefly de- 
scribed by saying that the function possesses an infinite deri- 




Fig. io 



Fig. II 



vative, or the derivative oo, at the point in question; we should 
remember, however, that this merely means that as h tends to 
the difference quotient increases beyond all bounds, and that the 
derivative in the sense in which we have denned it really does 
not exist. The geometrical meaning of an infinite derivative is 
that the tangent to the curve is vertical (cf. fig. 10). 

The function y = f(x) = -y/x, which is defined and con- 
tinuous for x 2^ 0, is also non-differentiable at the point x = 0. 
Since y is undefined for negative values of x, we here consider 

the right-hand derivative only. The equation •LLi — ■LL-l = 

h \/h 

shows us that this derivative is infinite; the curve touches the 

y-axis at the origin (fig. 11). 

Finally, in the function y = y/x 2 = a;* we have a case in 

which the right-hand derivative at the point x = is positive 



II] 



THE DERIVATIVE 



99 



and infinite, while the left-hand derivative is negative and 
infinite, as follows from the relation 

h fyh' 

As a matter of fact, the 
continuous curve y = a;*, 
the so-called semi-cubical 
parabola or Neil's para- 
bola, has at the origin a 
cusp perpendicular to the 
x-axis (cf . fig. 12). Fig _ lfc _ Coip 

6. Higher Derivatives and their Significance. 

The derivative f'(x) of a function is itself a function of x, 
the graph of which we call the derived curve of the given curve. 
For example, the derived curve of the parabola y = jc 2 is a 





Fig. 13. — Derived curves of sin* and Cos* 



straight line, represented by the function y = 2x. The derived 
curve of the sine curve y = sina; is the cosine curve y = cosa;; 
similarly, the derived curve of the curve y = cosa; is the curve 
y = —sina;. (Any of these latter curves can be obtained from 
the others by translation in the direction of the a:-axis, as is 
shown in fig. 13.) 



loo FUNDAMENTAL IDEAS [Chap. 

It is now quite a natural step to form the derived curves 
of the derived curves, i.e. to form the derivative of the function 
f'(x) = <f>(x). This derivative 

m=^ f{x+h) ~ f ' {x \ 

A-»-0 h 

provided that it really exists, we shall call the second derivative 
of the function f(x), and we shall denote it by f"(x). 

Similarly, we may attempt to form the derivative of f"(x), 
the so-called third derivative of f(x), which we then denote by 
f'"(x). In the case of most functions of importance there is noth- 
ing to hinder us from imagining this process repeated as many 
times as we like, and from thus defining an n-th derivative f^"\x). 
Occasionally it will be convenient to call the function f(x) its 
own 0-th derivative.* 

If the independent variable is interpreted as the time t and 
the motion of a point is represented by means of the function 
f(t), the physical meaning of the second derivative is found to 
be the velocity with which the velocity f'(t) changes, or, as it is 
usually called, the acceleration. Later (pp. 158-159) we shall 
discuss the geometrical interpretation of the second derivative in 
detail. Here, however, we may note the following facts: at a 
point where f"{x) is positive, f'(x) increases as x increases; if, on 
the other hand, f"(x) is negative, f'(x) decreases as x increases. 

7. The Derivative and the Difference Quotient. 

The fact that in the limiting process which defines the deri- 
vative the difference Ax tends to is sometimes expressed by 
saying that the quantity Ax becomes infinitely small. This expres- 
sion indicates that the passage to the limit is regarded as a pro- 
cess during which the quantity Aa; is never zero, yet approaches 
zero as closely as we please. In Leibnitz's notation the passage 
to the limit in the process of differentiation is symbolically ex- 
pressed by replacing the symbol A by the symbol d, so that we 
can define Leibnitz's symbol for the derivative by the equation 

^=lim^. 
dx A*-»-oAa; 

* The terms second, third, . . . , n-th differential coefficient are also used; of. 
second footnote, p. 90. 



II] THE DERIVATIVE IOI 

If, however, we wish to obtain a clear grasp of the meaning of 
the differential calculus we must beware of regarding the deri- 
vative as the quotient of two quantities which are actually 
" infinitely small ". The difference quotient p. absolutely must 

be formed with differences Aa; which are not equal to 0. After 
the forming of this difference quotient we must imagine the 
passage to the limit carried out by means of a transformation or 
some other device. We have no right to suppose that first Ax 
goes through something like a limiting process and reaches a 
value which is infinitesimally small but still not 0, so that Ax 
and Ay are replaced by "infinitely small quantities" or "in- 
finitesimals " dx and dy, and that the quotient of these quanti- 
ties is then formed. Such a conception of the derivative is in- 
compatible with the clarity of ideas demanded in mathematics; 
in fact, it is entirely meaningless. For a great many simple- 
minded people it undoubtedly has a certain charm, the charm of 
mystery which is always associated with the word " infinite "; 
and in the early days of the differential calculus even Leibnitz 
himself was capable of combining these vague mystical ideas 
with a thoroughly clear understanding of the limiting process. 
It is true that this fog which hung round the foundations of the 
new science did not prevent Leibnitz or his great successors 
from finding the right path. But this does not release us from 
the duty of avoiding every such hazy idea in our building-up 
of the differential and integral calculus. 

The notation of Leibnitz, however, is not merely attractive 
in itself, but is actually of great flexibility and the utmost 
usefulness. The reason is that in many calculations and formal 
transformations we can deal with the symbols dy and dx 
in exactly the same way as if they were ordinary numbers. They 
enable us to give neater expression to many calculations which 
can be carried out without their use. In the following pages 
we shall see this fact verified over and over again, and shall 
find ourselves justified in making free and repeated use of it, 
provided we do not lose sight of the symbolical character of 
the signs dy and dx. 

For the second and higher derivatives also Leibnitz has 
devised a notation of great suggestiveness and practical utility. 
He thinks of the second derivative as the limit of the " second 



toa FUNDAMENTAL IDEAS TChap. 

difference quotient " in the following manner. In addition to 
the variable x we consider a^ = x -\- h and x 2 — x + 2fe. We 
then take the second difference quotient as meaning the first 
difference quotient of the first difference quotient, i.e. the ex- 
pression 

where y=f(%), y\=f{%-i), and y 2 =f(x 2 ). If we also write 
h = Aa; and y 2 — y t = Ay lt y 1 — y= Ay, we may appropriately 
call the expression in the last bracket the difference of the differ- 
ence of y or the second difference of y and write symbolically * 

V% — 2 Vi + V = A Vi — % = A( A 30 = Afy 

In this symbolic notation the second difference quotient is then 

A 2 w 
written — — , where the denominator is really the square of Ax, 

(Aa;) 2 
while in the numerator the numbei 2 symbolically denotes the 
repetition of the difference process. This symbolism for the 
difference quotient f led Leibnitz to introduce the notation 

y ' ,==/ " (a!)= S' y, "= r{x)== % &o -' 

for the second and higher derivatives, and we shall find that this 
notation also stands the test of use. 



8. The Mean Value Theorem. 

Between the derivative -^ =f'(x) and the difference quotient 
ax 

there exists a simple relation which is important for many 

purposes. This relation is known as the mean value tficorem, 

* Here AA ~ A* is not a square, but merely a symbol for " difference of 
difference " or " seoond difference ". 

f We must emphasize that the statement that the second derivative may be 
represented as the limit of the second difference quotient requires proof. For 
we previously defined the seoond derivative, not in this way, but as the limit 
of the first difference quotient of the first derivative. In actual fact, the 
two definitions are equivalent, provided the second derivative is continuous; the 
proof, however, is not given, as we have no particular need of it here. 



II] 



THE DERIVATIVE 



103 




Fig. 14. — To illustrate the mean value 
theorem 



and is obtained in the following way. We consider the difference 
quotient 

/fa) -/fa) _ A/ 
x 1 — x 2 Ax 

of a function f{x), and assume that the derivative exists every- 
where in the interval x 1 g x ^ x 2 , so that the graph of the curve 
has a tangent everywhere. The 
difference quotient will be re- 
presented by the direction of the 
secant (see fig. 14); it is, in fact, 
the tangent of the angle a shown 
in the figure. Let us imagine 
this secant shifted parallel to 
itself. At least once it will reach 
a position in which it is a tangent 
to the curve at a point between 
x 1 and Og, namely, at the point 
of the curve which is at the 
greatest distance from the secant. Hence there will be an inter- 
mediate value £ such that 

/fa) ~/fa) ==_/•'(£). 
x^ x 2 

This statement is called the mean value theorem of the differential 
calculus. We can also express it somewhat differently by noticing 
that the number £ may be written in the form 

i = x 1 + d(x 2 — x 1 ), 

where is a certain number between and 1. In applications of 
the mean value theorem we shall often find that 6 cannot be 
more accurately determined than this, but it will usually turn 
out that a more accurate value is not needed. When accurately 
formulated, then, the mean value theorem runs as follows: 

If f(x) is continuous in the closed interval x x <i x gj x 2 and 
differentidble at every point of the open interval x x <x <x 2 , then 
there is at least one value 8, where <. 6 < 1, such that 

x » — "i 



104 



FUNDAMENTAL IDEAS 



[Chap. 



If we replace Xj by x and x 2 by x + h, we can express the 
mean value theorem by the formula 

f(x+h)-f(x}_ 



h 



= /'(!) =/'(*+«*), s<£<z+ft. 




Fig. 15. — To illustrate the mean 
value theorem 



We wish to emphasize that while it is essential that f(x) 
should be continuous for all points of the interval, including the 
end-points, we need not assume that the derivative exists at 
the end-points. This apparently trivial remark is actually useful 
in many applications. 

If at any point in the interior of the interval the derivative 
fails to exist, the mean value theorem is not necessarily true. 

This is shown by the example 
f(x) = \x\, p. 97. 

We can complete our intuitive 
argument by the following con- 
siderations. There is at least one 
point P on the curve which has 
the greatest possible distance from 
the chord joining the points on the 
curve whose abscissas are x 1 and 
x z (see fig. 15). At this point the 
curve by hypothesis has a definite tangent. We shall now 
prove that this tangent must be parallel to the chord. By 
definition the tangent is the limiting position of the secant 
and is obtained by joining P to a point Q on the curve 
and letting the point Q move towards P. Since by hypothesis 
Q is not farther from the chord than P, the line PQ produced 
in the direction P to Q must either out the chord or run parallel 
to it; and this must be the case, no matter on which side of P 
the point Q lies. This, however, is only possible if the limiting 
position is parallel to the chord. If we denote the abscissa of the 

point P by the letter £, the slope /'(£) of the tangent at P is then 

tt„ \ f/ x \ 

equal to the slope of the chord, -Li-Si — JK 2I - hence for the number 

a^ x 2 

I in the theorem we may simply take the abscissa of P. 

The rigorous proof of the mean value theorem is usually 
developed in the following way. We first establish Rolle's 
theorem, which is a special case of the mean value theorem: 

If a function ^(x) is continuous in the closed interval Xj ^ x ^ x 2 



II] THE DERIVATIVE 



io 5 



and differentiable in the open interval x 1 <x<x 2 , and if in 
addition ^(x,) =- and <f>(x 2 ) = 0, then there exists at least one 
point £ in the interior of the interval at which <£'(£) = 0. 

In fact, there must be at least one point £ interior to the 
interval, at which the function $(x) takes on its greatest or its 
least value (cf. Chap. I, Appendix I, § 2, p. 63); to be specific, 
we assume that g is a point where </>(£) is a maximum, so that 
for every x in the interval <f>(x) <; <£(£). Then for every number 
h whose absolute value | h | is small enough it is certainly true 
that <f>(£) — <f>($ + h)^0. If A is positive, 

h 

we now let h tend to zero through positive values and 
obtain $'(£) ^ 0. If, on the other hand, h is negative, 

t 2S 0, and thus by letting h tend to zero 

through negative values we obtain <£'(£) ^ 0; comparing this 
with the preceding inequality, we see that <j>'{g) = 0, which 
establishes our theorem. 

We now apply Rolle's theorem to the function * 

m =m -fix,) - ^1 {f(x 2 ) -f (Xl )}. 

This function obviously satisfies the condition <j>{xj = ^(a^) = 0, 
and is of the form <£ (x) = f(x) + ax + b with constant coefficients 
a = _ /fa) -/fa) and 6 By p 96) we know that 

<f>'(x) =/'(«) + a, 
and thus by Rolle's theorem we have 

0= ?(€)=*/'(£) + a 
for a suitably chosen intermediate value £ hence 

/'(^-^/faO-Zfa), 

a^ x, 
and the mean value theorem is proved. 

• * T^" 8 ,*" 111011011 " a I»rt from a factor independent of *, is the distance of the 
point (x, /(a:)) of the curve from the secant; the reader can easily verify this 
for himself. * 



io6 FUNDAMENTAL IDEAS [Chap. 

As the first of many applications of the mean value theorem we shall 
prove the foEowing. Let the function f(x) be continuous in the closed interval 
a ^ x ^ b and have a derivative f '(x) at every point of the open interval 
a < x < b. Then if f'(x) is positive everywhere in a < x < b, the function 
f(x) m monotonia increasing in the interval a^ x5S b; and likeunse if 
f'(x) w negative in a < x < b, then f(x) is monotonia decreasing. 

We shall prove the first statement; the second can be proved in 
a similar way. Suppose that f'(x) > 0, and let x t and x 2 > x^ be any two 
values of a; in the closed interval. Then by the mean value theorem 

/ta>-/(*i)-(*-*i)/m 

where x x <\ < x 2 . Since both factors on the right are positive, this 
proves that f(x t ) > /(a^); hence f(x) is monotonic increasing. 

9. The Approximate Representation of Arbitrary Functions by 
Linear Functions. Differentials. 

fix -+- h) f (x) 

The equation Yao. JK ' — =^— =/'( a; ) defining the deri- 

vative is equivalent to the equations 

Xx+h)-m=hf(x) + ch 

or y + Ay = fix + Ax) = /(*) + f'(x) Ace + e Aa;, 

where e is a quantity which tends to zero with h = Ax. If 
for the moment we think of the point x as fixed and the incre- 
ment Ace as variable, then by this formula the increment of the 
function, that is, the quantity Ay, consists of two terms, namely, 
a part hf'{x) which is proportional to h, and an " error " which 
can be made as small as we please relative to h by making A 
itself small enough. Thus the smaller the interval about the 
point x which we consider, the more accurately is the function 
f[ x _|_ %} (which is a function of h) represented by its linear part 
f(x) + hf'{x). This approximate representation of the function 
f(x -f- h) by a linear function of h is expressed geometrically by 
the substitution for the curve of its tangent at the point x. Later, 
in Chapter VII, we shall consider the practical application of 
these ideas to the performance of approximate calculations. 

Here we merely remark in passing that it is possible to use 
this approximate representation of the increment Ay by the 
linear expression hf'(x) to construct a logically satisfactory 
definition of the notion of a " differential ", as was done by 
Cauchy in particular. 



II] 



THE DERIVATIVE 



107 



While the idea of the differential as an infinitely small quan- 
tity has no meaning, and it is accordingly futile to define the 
derivative as the quotient of two such quantities, we may still 
try to assign a sense to the equation /'(a;) = dyjdx in such a way 
that the expression dyjdx need not be thought of as purely 
symbolic, but as the actual quotient of two quantities dy and dx. 
For this purpose we first define the derivative f\x) by our limit- 
ing process, then think of a; as fixed and consider the increment 
h =s Aa: as the independent variable. This quantity h we call 
the differential of x, and write h — dx. We now define the ex- 
pression dy—y'dx — hf'(x) as the differential of the function y; 
dy is therefore a number which has nothing to do with infinitely 
small quantities. So the derivative «j 
l/ =/'(a ; ) is now really the quotient 
of the differentials dy and dx; but 
in this statement there is nothing 
remarkable; it is, in fact, merely 
a tautology, a restatement of the 
verbal definition. The differential 
dy is accordingly the linear part of 
the increment Ay (see fig. 16). 

We shall not make any im- 
mediate use of these differentials. 
Nevertheless, it may be pointed out for the sake of completeness 
that we may also form second and higher differentials. For if 
we think of h as chosen in any manner, but always the same 
for every value of x, then dy — hf'(x) is a function of x, of which 
we can again form the differential. The result will be called 
the second differential of y, and will be denoted by the symbol 
dh] = dJf(x). The increment of hf'{x) being h{f'(x + h) —f'(x)}, 
the second differential is obtained by replacing the quantity in 
brackets by its linear part hf"(x), so that d?y = hj"(x). We 
may naturally proceed further along the same lines, obtaining 
third, fourth, — differentials of y, &c, which can be defined 
by the expressions Wf'"{x), Wf iv (x), and so on. 

10. Remarks on Applications to the Natural Sciences. 

In the applications of mathematics to natural phenomena 
we never have to deal with sharply defined quantities. Whether 
a length is exactly a metre is a question which cannot be decided 




x x+h 

Fig. 16. — The differential dy 



108 FUNDAMENTAL IDEAS [Chap. 

by any experiment and which consequently has no "physical 
meaning ". Again, there is no immediate physical meaning in say- 
ing that the length of a material rod is rational or irrational; we 
can always measure it with any desired degree of accuracy in 
rational numbers, and the real matter of interest is whether or 
not we can manage to perform such a measurement using rational 
numbers with relatively small denominators. Just as the ques- 
tion of rationality or irrationality in the rigorous sense of " exact 
mathematics " has no physical meaning, so the actual carrying 
out of limiting processes in applications will usually be nothing 
more than a mathematical idealization. 

The practical significance of such idealizations lies chiefly 
in the fact that if they are used all analytical expressions 
become essentially simpler and more manageable. For example, 
it is vastly simpler and more convenient to work with the 
notion of instantaneous velocity, which is a function of only 
one definite time-instant, than with the notion of average 
velocity between two different instants. Without such idealiza- 
tion every rational investigation of nature would be condemned 
to hopeless complications and would break down at the very 
outset. 

We do not intend, however, to enter into a discussion of the 
relationship of mathematics to reality. We merely wish to 
emphasize, for the sake of our better understanding of the theory, 
that in applications we have the right to replace a derivative 
by a difference quotient and vice versa, provided only that the 
differences are small enough to guarantee a sufficiently close 
approximation. The physicist, the biologist, the engineer, or 
anyone else who has to deal with these ideas in practice, will 
therefore have the right to identify the difference quotient 
with the derivative within his limits of accuracy. The smaller 
the increment h = dx of the independent variable, the more 
accurately can he represent the increment Ay =f(x + h) —f(x) 
by the differential dy = hf'(x). So long as he keeps within the 
limits of accuracy required by the problem, he is accustomed 
to speak of the quantities dx=h and dy = hf'(x) as " infinitesi- 
mals ". These " physically infinitesimal " quantities have a 
precise meaning. They are finite quantities, not equal to zero, 
which are chosen small enough for the given investigation, 
e.g. smaller than a fractional part of a wave-length or smaller 



II] THE DERIVATIVE 109 

than the distance between two electrons in an atom; in general, 
smaller than the degree of accuracy required. 



Examples 

1.* Replace the statement " At the point x = Z, the function f(x) is 
not differentiable " by an equivalent statement not using any form of 
the word "differentiable". 

2. Differentiate the following functions directly by using the de- 
finition of the derivative: 

( '».TT m +T* W^TT W^-,. 

(e) sin 3a;. (/) cosaz. (0) sin 2 a;. (A) cos 2 *. 

3. Find the intermediate value £ of the mean value theorem for the 
following functions, and illustrate graphically: 

(a) 2x. (6) *». (c) 5a? + 2x. (d) l/(z*+ 1). (e) x 1 ' 3 . 

4. Show that the mean value theorem fails for the following functions 
when the two points are taken with opposite signs, e.g. x 1 = —I, x =1: 

(a) l/x. (b) |*|. (c) ar" 3 . 
Illustrate graphically, and compare with the previous example. 

4. The Indefinite Integral, the Peimitive Function, and 
the Fundamental Theorems of the Differential and 
Integral Calculus. 

As we have already mentioned above, the connexion between 
the problem of integration and the problem of differentiation is 
the corner-stone of the differential and integral calculus. This 
connexion we will now study. 

1. The Integral as a Function of the Upper Limit. 

The value of the definite integral of a function /(a;) depends on 
the choice of the two limits of integration a and b. It is a func- 
tion of the lower limit a as well as of the upper limi t, b. In order 
to study this dependence more closely we imagine the lower 
limit a to be a definite fixed number, denote the variable of in- 
tegration no longer by x but by u (cf. p. 82), and denote the upper 
limit by x instead of b in order to suggest that we shall let the 



no 



FUNDAMENTAL IDEAS 



[Chap. 



upper limit vary and that we wish to investigate the value of 
the integral as a function of the upper limit. Accordingly, we 
write 



f*f(u)du = <!>(x). 



V 



^%' m 







l/////////////, 



Fig. 17 



We call this function <3>(x) an indefinite integral of the function 

f(x). When we speak of an and 
not of the indefinite integral, we 
suggest that instead of the lower 
limit a any other could be chosen, 
in which case we should ordi- 
narily obtain a different value 
for the integral. Geometrically 
the indefinite integral for each 
value of x will be given by the 
H area (shown by shading in fig. 17) 
under the curve y=f{u) and 
bounded by the ordinates u = a 

and u = x, the sign being determined by rules given earlier 

(p. 81). 

If we choose another lower limit a in place of the lower limit 

a, we obtain the indefinite integral 

T(x)=£f(u)du. 

The difference T(a;) — Q>(x) will obviously be given by 

J f(u)du, 

which is a constant, since a and a are each taken as fixed given 
numbers. Therefore 

y F(x) = 0(x) + const.; 

Different indefinite integrals of the same function differ only 
by an additive constant. 

We may likewise regard the integral as a function of the lower 
limit, and introduce the function 

<t>{x) = ff(u)du, 
in which b is a fixed number. Here again two such in- 



II] THE INDEFINITE INTEGRAL m 

tegrals with different upper limits b and j8 differ only by an 
additive constant / f(u)du. 

2. The Derivative of the Indefinite Integral. 

We will now differentiate the indefinite integral <&{x) with 
respect to the variable x. The result is the following theorem: 

The indefinite integral 

^(x) = ff{u)du 

J a 

of a continuous function f(x) always possesses a derivative <D'(x), 
and, moreover, 

thai is, differentiation of the indefinite integral of a given con- 
tinuous function always gives us back that same function. 



a xx, XgX+h. x 

Fig. 1 8. — Differentiation of the indefinite integral 

This is the root idea of the whole of the differential and integral 
calculus. The proof follows extremely simply from the inter- 
pretation of the integral as an area. We form the difference 
quotient 

Q(x+h) — Q(x) 
h 
and observe that the numerator 

<S>(x+h) - «(x) =f* +h f{u)du-£f(u)du=f +h f{u)du 

is the area between the ordinate corresponding to x and the 
ordinate corresponding to x + h. 

Now let x be a point in the interval between x and x + h at 
which the function f(x) takes its greatest value, and x 1 a point 
at which it takes its least value in that interval (cf. fig. 18). 



ri 2 FUNDAMENTAL IDEAS [Chap. 

Then the area in question will lie between the values hf(x ) and 
hfixj), which represent the areas of rectangles with the interval 
from xtoic + Aas base and/(a: ) and/fo) respectively as alti- 
tudes. Expressed analytically, 

/ W £ »<« + *>-» ( 'W (»j. 

This can also be proved directly from the definition of the in- 
tegral without appealing to the geometrical interpretation.* 
To do this we write 

x+h « 

/(«) du = lim 2/(w„) Aw„, 



r 



where u = x, u v u 2 , . . . , u„ = x + h are points of division of 
the interval from x to x -f h, and the greatest of the absolute 
values of the differences Aw„ = w„ — u v _ x tends to zero as n 
increases. Then A.u v /h is certainly positive, no matter whether 
h is positive or negative. Since we know that/(a; ) ^/(m„) ^ /(%) 
and since the sum of the quantities Am„ is equal to h, it follows 
that 

and thus if we let n tend to infinity we obtain the inequalities 
stated above for 

r x+h ,, v , ®(x+h) — <X>(x) 
1 f '" A iu or — - 1 . 



* f f(u)dv 



If A now tends to zero, both f(x ) and f{xj must tend to the 

limit f(x), owing to the continuity of the function. We therefore 

see at once that 

... . ,. <S>(x+ h) — ®(x) ,, . 
«D'(a;) = hm v ^ ' y -L=f{x), 

h->0 "■ 

as stated by our theorem. 

Owing to the differentiability of <&(x), we have the following 
theorem, by § 3, No. 5, p. 97: 

The integral of a continuous function f(x) is itself a continuous 
function of the upper limit. 

* Compare also the later discussion on p. 127. 



II] THE INDEFINITE INTEGRAL 113 

For the sake of completeness we would point out that if we 
regard the definite integral not as a function of its upper limit 
but as a function of its lower limit, the derivative is not equal 
to f(x), but is instead equal to —f(x). In symbols: if we put 

H x )=\ f(u)du, 
then <j>'(x)= — f(x). 

The proof follows immediately from the remark that 
ff(u)du = — lf(u)du. 

3. The Primitive Function; General Definition of the Indefinite 
Integral. 

The theorem which we have just proved shows us that the 
indefinite integral O(x) at once gives the solution of the follow- 
ing problem: given a function f (x), to determine a junction F(x) 
such that 

F'(x)=f(x). 

This problem requires us to reverse the process of differentiation. 
It is a typical inverse problem such as occurs in many parts of 
mathematics and such as we have already found to be a fruitful 
mathematical method for generating new functions. (For ex- 
ample, the first extension of the idea of natural numbers was 
made under the pressure of the necessity for reversing certain 
elementary processes of calculation. The formation of inverse 
functions has led and will lead us to new kinds of functions.) 

A function F(x) such that F'(x) =f{x) is called a primitive 
function of f(x), or simply a primitive of f(x); this terminology 
suggests that the function /(a;) arises from F(x) by differentiation. 

This problem of the inversion of differentiation or of the 
finding of a primitive function is at first sight of quite a different 
character from the problem of integration- From p. Ill, however, 
we know that: 

Every indefinite integral O(x) of the function f(x) is a primitive 
o/f(x). 

Yet this result does not completely solve the problem of find- 
ing primitive functions. For we do not yet know if we have 
found all the solutions of the problem. The question about the 

s (E798) 



"4 FUNDAMENTAL IDEAS [Chap. 

group of all primitive functions is answered by the following 
theorem, sometimes referred to as the fundamental theorem of 
the differential and integral calculus: 

The difference of two primitives F x (x) and F 2 (x) of the same func- 
tion f (x) is always a constant: 

F^x) - F 2 {x) = c. 

Thus from any one primitive function ~E(x) we can obtain all the 
others in the form 

F(x) + c 

by suitable choice of the constant c. Conversely, for every value of 
the constant o the expression F x (x) = F(x) + c represents a primi- 
tive function ofi(x). 

It is clear that for any value of the constant c the function 
F(x) + c is a primitive, provided that F(x) itself is one. For 
(cf. p. 96) we have 

{ F(x + h) + c> - {F{x) + c} _ F(x +h)- F(x) 
h h 

and since by hypothesis the right-hand side tends to/(a;) as h -*■ 0, 
so does the left-hand side, and therefore 

l{F(x) + c}=f(x) = F'(x). 

Thus to complete the proof of our theorem it only remains 
to show that the difference of two primitive functions F x (x) and 
F 2 (x) is always a constant. For this purpose we consider the 
difference 

FM-FJM^Glx) 

and form the derivative 

G'(x) = lim f *i(g +*)-*!(*) _ F 2 (x + h)-F 2 (x) \ 
h-+o\ h h y 

Both the expressions on the right-hand side, by hypothesis, have 
the same limit /(x) as h -> 0; thus for every value of x we have 
G'(x) = 0. But a function whose derivative is everywhere zero 
must have a graph whose tangent is everywhere parallel to the 
x-axis, i.e. must be a constant; and therefore we have G(x) = c, 



II] THE INDEFINITE INTEGRAL 115 

as we stated above. We can prove this last fact without relying 
upon intuition, by using the mean value theorem. Applying the 
mean value theorem to G(x), we have 

G(x 2 ) - CHxJ = (x 2 - xJG'd); x 1 <$<x a . 

But we have seen that the derivative G'(x) is equal to for every 
value of x, and hence in particular for the value £; hence it follows 
immediately that G(x 1 ) = G(x 2 ). Since x l and x 3 are arbitrary 
values of a; in the given interval, G(x) must be a constant. 

Combining the theorem just proved with the result of No. 2 
(p. Ill), we can now make the following statement: 

Every primitive function F(x) of a given function f (x) can be 
represented in the form 

F(x) = c + <D (*) = c + £f{u)du, 

where c and a are constants, and conversely, for any constant values 
of a and c chosen arbitrarily this expression always represents a 
primitive function. 

It may readily be guessed that the constant c can as a rule 
be omitted, since by changing the lower limit a we change the 
primitive function by an additive constant. In many cases, 
however, we should not obtain all the primitive functions if 
we omitted the c, as the example f(x) = shows. For this 
function the indefinite integral of No. 1 (p. 110) is always 0, inde- 
pendently of the lower limit; yet any arbitrary constant is a 
primitive function of f(x) = 0. A second example is the func- 
tion f(x) = -y/jc, which is defined for non-negative values of x 
only. The indefinite integral is 

^(x) = fx m -§a sl \ 

and we see that no matter how we choose the lower limit a the 
indefinite integral <D(a;) is always obtained from § (a;) 3 ' 2 by addition 
of a constant which is less than or equal to zero, namely, the con- 
stant — §a s/2 ; yet such a function as §a; 3/2 + 1 is also a primi- 
tive function for y/x. Thus in the general expression for the 
primitive function we cannot dispense with the additive constant. 
The relationship which we have found suggests an extension 
of the idea of the indefinite integral. We shall henceforth call 

every expression of the form c + Q>(x) = c -f- / f(u)du an hide- 



n6 FUNDAMENTAL IDEAS [Chap. 

finite integral of f(x). In other words, we shall no longer make any 
distinction between the primitive function and the indefinite in- 
tegral. Nevertheless, if the reader is to have a proper under- 
standing of the interrelations of these concepts it is absolutely 
necessary that he should clearly bear in mind that in the first 
instance integration and inversion of differentiation are two 
entirely different things, and that it is only the knowledge of 
the relationship between them that gives us the right to apply 
the term " indefinite integral " to the primitive function also. 
It is customary to represent the indefinite integral by a 
notation which in itself is perhaps not perfectly clear. We write 

F(x) = c + fj(u)du=ff(x)dx; 

that is, we omit the upper limit x and the lower limit a and also 
the additive constant c and use the letter x for the variable of 
integration. It would really be more consistent to avoid this 
last change, in order to prevent confusion with the upper limit x 
which is the independent variable in F(x). In using the notation 
ff(x)dx we must never lose sight of the indeterminacy con- 
nected with it, i.e. the fact that that symbol always denotes an 
indefinite integral only. 

4. The Use of the Primitive Function in the Evaluation of 
Definite Integrals. 

Suppose that we know any one primitive function F(x) = 

ff(x)dx for the function /(a;) and that we wish to evaluate the 

definite integral Jf(u)du. "We know that the indefinite integral 

Ja 

being also a primitive of f{x), can only differ from F(x) by an 
additive constant. Consequently 

<b(z) = F(x) + e, 
and the additive constant c is at once determined if we recollect 

rx 

that the indefinite integral <J>(aj)= / f(u)du must take the 
value when x = a. We thus obtain = (a) = F(a) + c, 



II] THE DEFINITE INTEGRAL 117 

whence c=—F(a) and O (a;) = F(x) — F(a). In particular, 
for the value x= b we have 



f b f(u)du=F(b)-F(a), 



which gives us the important rule: 

If F(x) is any -primitive of the function i(x) whatsoever, 
the definite integral of f (x) between the limits a and b is equal to the 
difference F(b) — F(a). 

If we use the relation F'(x) =f{x) this may be written 
in the form 

Fib) - F(a) = f F'{x)dx = f* d -^ dx. 

Ja Ja dx 

This formula can easily be proved and understood directly. We 
divide the interval a <S x fS b into sub-intervals Ax 1 , Ax 2 , . . . , Ax n , 

A EI 

and consider the sum S — Aa;„. On the one hand, this sum is 
Ax v 

simply S AF = F(b) — F(a), independently of the particular 

subdivision; hence its limit is F(b) — F(a). On the other hand, 

its limit is also equal to / F'(x) dx, as follows from the mean value 

theorem. For AF/Ax„ = F'(£ v ), where f„ is a point intermediate 
between the ends x v _ x and x v of the interval Ax„. The sum is 
therefore equal to S Aa;„ F'(i y ); and by the definition of integral 

this tends to the limit / F'(x)dx as the subdivision is made finer, 

"a 

which establishes our formula. 

In applying our rule we often use the symbol | to denote 
the difference F(b) — F (a); i.e. we write 

f(x)dx = F(b) - F(a) = F(x) 



jO 



meaning by the vertical line that in the preceding expression 
first the value b, and then the value a, is to be substituted for x, 
and finally the difference of the resulting numbers is to be found. 

5. Examples. 

We are now in a position to illustrate by a series of simple 
examples the relationships between the definite integral, the 
indefinite integral, and the derivative, which we have just in- 



n8 FUNDAMENTAL IDEAS [Chap. 

vestigated. In virtue of the theorem on p. Ill, from each of 
the integration formulae directly proved in § 2 (p. 82) we can 
derive a differentiation formula. 

On p. 86 we obtained the integration formula 



£ 



x*dx = (6»+ 1 — a** 1 ) 

a+ 1 



for every rational number a 4= 1 and all positive values of a and 6; if we 
replace the variable of integration by « and the upper limit by x, this may 
be written 



£' 



u" du = (a;^ 1 — a"* 1 ). 

oc -f~ 1 



Prom this it follows by the fundamental theorem that the right-hand side 
is a primitive function of the integrand, i.e. the differentiation formula 

d 

— z«+i = (« + l)a?» 

ax 

is valid for every rational value of a 4= — 1 and all positive values of x. 
By direct substitution we find that this last formula is also true for 
a = — 1, if x > 0. The result obtained exactly agrees with what we have 
already found (p. 95) by direct differentiation. Thus by using the fun- 
damental theorem after we had carried out the integration, we could have 
saved ourselves the trouble of that differentiation. 
Further, from the integration formula 



"a 



cos u du = sin x — sin a 

given on p. 87 it follows that — sin x = cos x, in agreement with the 
result found on p. 96. *" 

Conversely, however, we may regard every directly-proved differen- 
tiation formula F'(x) = f(x) as a connexion between a primitive function 
F(x) and a derived function f(x), that is, we may regard it as a formula 
for indefinite integration and then obtain from it the definite integral of 
f(x) as on p. 117. This very method is frequently made use of, as we 
shall see in Chapter IV (p. 205). In particular, we may start from the 
results of § 3 (p. 94) and obtain the integral formulae of § 2, p. 82, in virtue 
of the fundamental theorem. For example, from p. 95 we know that 
d x*+ 1 

— 1'+» = (a + l)a; a . Therefore — — - is a primitive function or indefinite 
ax a. + 1 

integral of x a , provided that a #= — 1, and thus by p. 117 we again arrive 
at the integral formula above. 



II] 



GRAPHICAL INTEGRATION 

Examples 



"9 



1. From the differentiations performed in Examples 2, 3 on p. 109, set 
np the corresponding integrations. 

2. Evaluate (a) /* ** - (6) /* **** . 

3. Using Example 2, prove from the definition of the definite integral 
that 

(a) Mm nf - + I + . . . + —1 = -. 

.-».- L(w + 1)* ^ (n + 2) 2 T T (2»)*J 2 

(6) lim n*\ l - + ? + . . . + - 1 = J 



5. Simple Methods of Graphical Integration 

An indefinite integral or primitive function of f(x) is a func- 
tion y = F{x) which not only can be visualized as an area, but 
like any other function can be represented graphically by a 
curve. Our definition immediately suggests the possibility of 
constructing this curve approxi- 
mately and thus obtaining a graph 
of the integral function. To begin 
with we must remember that this 
last curve is not unique, but on 
account of the additive constant 
can be shifted parallel to itself 
in the direction of the #-axis. We 
can therefore require that the in- 
tegral curve shall pass through 
an arbitrarily selected point, e.g. if x = 1 belongs to the 
interval of definition of f(x), through the point with the 
co-ordinates x = 1, y = 0. The curve is thereafter determined 
by the requirement that for each value of x its direction is given 
by the corresponding value of f(x). To obtain an approximate 
construction of a curve which satisfies these conditions, we seek 
to construct not the curve y = F(x) itself, but a polygonal path 
(broken line) whose corners lie vertically above previously as- 
signed points of division of the z-axis and whose segments have 
approximately the same direction as the portion of the integral 
curve between the same points of division. For this purpose we 




Fig. 19. — Graphical integration 



120 



FUNDAMENTAL IDEAS 



[Chap. 

divide our interval of the 2>axis by means of the points x = 1, 
x l , aj 2 > • • • m to a certain number of parts, not necessarily all 




Fig. 20. — Graphical integration of 

of the same length, and at each point of division we erect the 
parallel to the y-axis. Then (fig. 19) we draw through the point 
x = 1, y = the straight line whose slope is equal to /(l); 

through the intersection of 
this line with the line x=x 1 
we draw the line with the 
slope /(a^); through the in- 
tersection of this line with 
x = a? 2 we draw the line with 
slope f(x 2 ), and so on. In 
the actual practical con- 
struction of these lines, we 
erect at each point of divi- 
sion the ordinate to the 
curve y=f(x), and project 
these ordinates on to any 
parallel to the y-axis; to 
be specific, let us suppose 
that they are projected on to 
the y-axis itself. We then obtain the direction of the integral 
curve by joining the point with co-ordinates x= and y—f(x) 
to the point x = — 1, y = 0. By carrying over these directions 



y, 










y- 


x / 










1 




/ 




/ 


1 
1 

y 

1 

1 










/ 








"71 ' 


/ 


1 
1 
1 
1 
1 


1 
1 
1. 


-/{■ 


1 

1 
1 








1 yt ~x 


1 


/ 


\ 




V 











Fig. ai. — Graphical integration of * 



II] GRAPHICAL INTEGRATION 121 

parallel to themselves we obtain a polygonal path whose corners 
lie vertically above the given points of division of the a;-axis and 
whose direction agrees with the direction of the integral curve at 
the initial point of each interval. This polygonal path can be made 
to represent the integral curve with any desired degree of accuracy 
by making the subdivision of the interval fine enough. We can 
frequently improve the accuracy of the construction by choosing 
for the direction of each segment of the polygon that direction 
which belongs not to the beginning but to the mid-point of the 
corresponding interval (cf. figs. 20 and 21).* 

In fig. 21 the construction described above is carried out for the func- 
tion /(x) = x. By graphical integration we obtain an approximation to the 
integral curve, which is the parabola y = $x* — J. In addition, fig. 20 
shows an approximation to the integral function of the function /(a;) = 1/x. 
We shall study this integral later in greater detail — it will turn out to be 
the logarithmic function. Finally, the reader would be well advised to 
work out some other examples for himself, e.g. the graphical integration 
of the functions sin x and cos x. 

Examples 

1. By graphical integration with the interval h = -fe construct the 
following integral curves: 

(a) fa 2 dx (0 <^ x <^ 2). (6) J* jj dx (1 <^ x <£ 2). 

W F T^dx (0^x^,1). 

■'0 * ~> * 

r 1 1 

In particular, evaluate / — - — - dx. 
J n 1 -f- x 



6. Further Eemarks on the Connexion between the 
Integral and the Derivative 

Before we begin to follow up the relationships found in § 4 

(p. 109) systematically we shall illustrate them from another 

point of view, which is closely related to the intuitive idea of 

density and to other physical concepts. 

* We may mention in passing that graphical integration (that is, the find- 
ing of the graph of a primitive F(x) of a function f(x) which is itself given by 
a graph) can also be performed by means of a mechanical device, the so-called 
integraph. In this mechanism a pointer is moved along the given curve and 
a pen automatically traces one of the curves y = F(x) for which F'(x)=f(x). 
The indeterminacy of the constant of integration is expressed by a certain arbi- 
trariness in the initial position of the instrument. For integrating devices 
generally see B. Williamson, Integral Calculus, pp. 214-217 (Longmans); Dic- 
tionary of Applied Physics, Vol. Ill, pp. 450^457 (Maemillan, 1923). 
6* (1798) 



i22 FUNDAMENTAL IDEAS [Chap. 

1. Mass Distribution and Density; Total Quantity and Specific 
Quantity. 

We suppose that any mass whatsoever is distributed along 
a straight line, the a;-axis, the distribution being continuous but 
not necessarily uniform. We may, for example, think of a vertical 
column of air standing on a surface of area 1; as a>axis we take 
a line pointing vertically upwards and as origin the point on 
the earth's surface. The total mass between two abscissae x 1 
and x 2 is then determined in the following way by means of 
a so-called sum-function F(x). We measure distance along the 
sine from the initial point of the mass-distribution, x — 0, and 
by F(x) we mean the total mass between the abscissa and 
the abscissa x. The increment of mass from the abscissa Xj to 
the abscissa x z is then given simply by 

F(x 2 ) - F(zJ; 

a sign is thus assigned to the increment, and this sign changes 
if x 1 and x 2 are interchanged. 

The average mass per unit length in the interval x 1 to x 2 is 

F(x 2 )-F(xJ ^ 

If we assume that the function F(x) is differentiable, then as 
x 2 -^x 1 this value tends to the derivative F'lxj). This quantity 
is precisely what is usually called the specific mass or density 
of the distribution at the point a^; as a rule, of course, its value 
depends on the particular point chosen. Between the density 
f(x) and the sum-function F(x) there accordingly exists the 
relation 

F(x) =£f(u)du; f(x) = F'(x). 

The sum-function is a primitive function of the density, or, 
what amounts to the same thing, the mass is the integral 
of the density; conversely, the density is the derivative of the 
sum-function. 

Exactly the same relation is very frequently encountered 
in physics. For example, if by Q(t) we denote the total amount 
of heat needed to raise unit mass of a substance from tempera- 



II] INTEGRAL AND DERIVATIVE 123 

tare t to temperature t, then to raise the temperature from t^ 
to t 2 an amount of heat equal to 

is needed. Between ^ and t 2 the average amount of heat used 
per unit increase in temperature is then 



If we once again assume the differentiability of the function 
Q (t) we obtain in the limit a function 

which we call the specific heat of the substance. This specific 
heat is in general to be regarded as a function of the tem- 
perature. 

Here again, between specific heat and total quantity of heat 
there exists the characteristic relation of integral and derivative, 



f b q(t)dt=Q{b)-Q(a). 



We shall meet with the same relations in all cases where 
total quantity and specific quantity are contrasted, e.g. 
electric charge as contrasted with density of charge, or the 
total force on a surface as contrasted with the force-density or 
pressure. 

In nature it usually happens that what we know directly is 
not the density or specific quantity, but the total quantity; thus 
it is the integral which is primary (as the name " primitive " 
suggests) and the specific quantity is only arrived at after a 
limiting process, namely, differentiation. 

Incidentally it may be noted that if the masses considered 
are by their nature positive, the sum-function F(x) must be a 
monotonic increasing function of x, and consequently the specific 
quantity, the density /(as), must be non-negative. Nothing hinders 
us, however, from considering negative quantities also (e.g. 
negative electricity); then our sum-functions F{x) need no longer 
be monotonic. 



i24 FUNDAMENTAL IDEAS [Chap. 

2. The Question of Applications. 

The relation of the primitive sum-function to the density of 
distribution perhaps becomes clearer when it is realized that 
from the point of view of physical facts the limiting processes 
of integration and differentiation represent an idealization, and 
that they do not express anything exact in nature. On the con- 
trary, in the realm of physical actuality we can form in place of 
the integral only a sum of very many small quantities and in 
place of the derivative only a difference quotient of very small 
quantities. The quantities Ax remain different from 0; the 
passage to the limit Ace -> is merely a mathematical simplifi- 
cation, in which the accuracy of the mathematical representation 
of the reality is not essentially impaired. 

As an example we return to the vertical column of air. Ac- 
cording to the atomic theory we find that we cannot think of 
the distribution of mass as a continuous function of ce. On the 
contrary, we will assume (and this, too, is a simplifying ideali- 
zation) that the mass is distributed along the cc-axis in the form 
of a large number of point-molecules lying very close to one 
another. Then the sum-function F(x) will not be a continuous 
function, but will have a constant value in the interval between 
two molecules and will take a sudden jump as the variable x 
passes the point occupied by a molecule. The amount of this 
jump will be equal to the mass of the molecule, while the average 
distance between molecules, according to results established in 
atomic theory, is of the order of 10 -8 cm. If now we are per- 
forming upon this air column some measurement in which masses 
of the order 10* molecules are to be considered negligible, our 
function cannot be distinguished from a continuous function. 
For if we choose two values x and x + Ax whose difference Ace 
is less than 10 -4 cm., then the difference between F{x) and 
F(x + Ace) will be the mass of the molecules in the interval; 
since the number of these molecules is of the order of 10 4 , the 
values of F{x) and F{x -f Ax) are, so far as our experiment is 
concerned, equal. As density of distribution we consider simply 

., ,.- ... AF(x) F(x+Ax)-F(x) . x . 

the difference quotient — = — i — ■ '- ^— '; it is an 

Asc Ax 

important physical assumption that we do not obtain measurably 

different values for this quotient when Ace is allowed to vary 



II] APPLICATIONS 



"5 



between certain bounds, say between 10~ 4 and 10~ 5 cm. Now 
let us imagine that F{x) is measured and plotted for a large 
number of points about 10 -4 cm. apart, and that the points thus 
found are joined by straight lines; we obtain a polygon, and 
by rounding off the corners we finally obtain a curve with a 
continuously turning tangent. This curve is the graph of some 
function, say F^x). This new function F x (x) cannot within the 
limits of experimental accuracy be distinguished from F(x), 
and its derivative is within the same limits equal to AF/Ax; 
we thus have found a continuous differentiable function which 
for the purposes of physics is the function F(x). 

It is perhaps appropriate to discuss yet another example of 
the concepts of sum-function and density of distribution. In 
statistics, e.g. in the kinetic theory of matter or in statistical 
biology, these concepts frequently occur in a form in which the 
nature of the mathematical idealization is particularly clear. 
Let us consider e.g. the molecules of a gas confined in a vessel 
and observe their velocities at a given instant of time. Let the 
number of molecules be N, and let the number of those with 
velocities less than x be N<t>(x). Then <J>(z) denotes the ratio of 
the number of molecules moving with velocities between and 
a; to the total number of molecules. This sum-function is, of 
course, not continuous, but is sectionally * constant and suddenly 
increases by 1/2V when x as it increases passes a value which 
is equal to the velocity of some molecule. 

The idealization which we shall make here is that we shall 
think of the number N as increasing beyond all bounds. We 
assume that in this passage to the limit N -> 00 the sum-function 
$(2:) tends to a definite continuous limit function F(x). That 
this is really the case (i.e. that we can with sufficient accuracy 
replace <J>(a;) by this continuous function F(x)) is obviously an 
important physical assumption; and it is another such assump- 
tion to suppose that this sum-function F(x) possesses a deri- 
vative F'(x)=f(x), which we then call the density of distri- 
bution. The sum-function is connected with the density of dis- 
tribution by the equations 

*(*) = fmdu; F(b) - F(a) = f f{x)dx. 
• Got. stUclctoeiie; of. Chap. IX, § 3. 



126 FUNDAMENTAL IDEAS [Chap. 

This density of distribution is occasionally referred to as the 
specific probability that a molecule possesses the velocity x. 
The idealization we have just carried out plays a great part in 
the kinetic theory of gases originated by Maxwell; in exactly 
the same mathematical form it appears in many problems of 
mathematical statistics. 

7. The Estimation of Integrals and the Mean Value 
Theorem of the Integral Calculus 

We close this chapter with some considerations about a matter 
of general significance, the whole importance of which will not 
appear until somewhat later. The point in question is the 
estimation of integrals. 

1. The Mean Value Theorem of the Integral Calculus. 

The first and simplest of these estimation rules runs as fol- 
lows: if in an interval a ^ x ^ b the continuous function /(as) 
is everywhere non-negative (is either positive or zero), then the 
definite integral 

f(x)dx 



f.> 



is also non-negative. Similarly, the integral is not positive if the 
function is positive nowhere in the interval. The proof of this 
theorem follows directly from the definition of the integral. 
From this the following theorem arises: if 

f(x)^g(x) 
everywhere in the interval a ^x<^b, then 

rf(x)dx Si / g(x)dx 
•'a 

also. For by our first remark the integral of the difference 
f(x) — g (x) is non-negative and by our addition rule (cf . p. 82) 

/ (f(x)—g(x))dx= I f{x)dx— f g{x)dx. 

Let M be the greatest and m the least value of the function 
f(x) in the interval ab. The function M — f(x) is non-negative 
in the interval, and the same is true for the function f(x) — m. 



II] THE ESTIMATION OF INTEGRALS 127 

From the above remark we immediately obtain the double 
inequality 

rmdx^ J f(x)dx^ j Mdx. 

But / mdx= ml dx= m(b — a) and likewise / M dx=M(b — a), 
whence m(b — a) ^ jf(x)dx ^M(b — a). The integral under 

•'a 

consideration can therefore be represented as the product of 
(6 — a) and some number p between m and M : 



f f(x)dx-- 

J a 



fi(b — a), m^fi^M. 



As a rule there is no need to state the exact value of this mean 
value fj.. We may, however, state that it will be assumed by the 
function at one point f of the interval a ^ £ ^ 6 at least, since 
in its interval of definition a continuous function assumes all 
values between its greatest value and its least. As in the case 
of the mean value theorem of the differential calculus, the exact 
statement of the value $ is in many cases unimportant. We may 
therefore put p = /(£), where £ is an intermediate value of x, 
and we then have 

ff(x)dx=(b-a)f(Z), a^i^b. 

This last formula is called the mean value theorem of the integral 
calculus. 

We can generalize the theorem somewhat by considering, 
instead of the integrand /(a;), an integrand of the form f(x) p (x), 
where p (x) is an arbitrary non-negative function, which, like f(x), 
is to be assumed continuous. Since mp(x) ^f(x)p(x) ^ Mp{x), 
we immediately obtain the relation 

m j p(x)dx <; j f(x)p(x)dx ^ M f p(x)dx, 

or, in a single equation, 

j" f{x)p{x)dx=f{£) f p(x)dx, 

J a Ja 

where £ is again a number intermediate between a and b. 



128 



FUNDAMENTAL IDEAS 



[Chap. 



W 




f 
f-e 



W© have thus proved the following theorem: 

If f(x) and p(x) are continuous junctions in a ^ x ^ b, amd 
p(x) ^ 0, <Aew 

f f(x)p{x)dx=m f V {x)dx, 

J a J a 

where a :g f 5S b. 

2. Applications. The Integration of x" for any Irrational Value 
of a. 

The mean value theorem and the equivalent integral estimates 
immediately afford us an insight into an intuitive and easily 

apprehended fact: the value 
of an integral changes very 
little if the function itself is 
everywhere changed very little. 
In precise language: if in the 
whole interval a ^ x ^ b the 
absolute value of the difference 
of two functions f(x) and g(x) 
is less than a number e, then 
the difference of their inte- 
grals is in absolute value less 
than e(b— a). In symbols: 
if throughout the interval 
a ^ x ^ b we have \f(x) — g(x) | < e, then 

f f(x)dx —J g(x)dx < e(b — a) 

or, otherwise expressed, 
— e(b — a) + fg{x)dx < jf(x)dx < lg(x)dx + e(b — a). 

Ja •* a Ja 

Fig. 22 illustrates this theorem very clearly. For the curve 
y=f{x) we draw the "parallel curves" y—f(x)-\-e and 
y = j(x) — e. By hypothesis the function g(x) keeps within the 
strip bounded by these " parallel curves ". It is clear from this 
that the areas which are bounded by the curves f(x) and g(x) 
differ from one another by less than half the area of the strip, 
and the area of the strip is just 



Fig. 23. — To illustrate the continuity 
of an integral 



II] THE ESTIMATION OF INTEGRALS 129 

f a {/(*) + e}d* -£{/(*>) - e ) dx = 2«(6 - a). 

No appeal to intuition is needed. Since 

-e + g(x)<f(x)<e + g(x)', 
it follows, by considerations analogous to those on p. 126, that 

£{-<■+ g(x)}dx <£f{x)dx <£{g(x) + e }dx, 

which as the result of the fundamental rules of integration takes 
the form 

— e(b — a) +£g(x) dx <Jf(x)dx < fg{x)dx + e(6 - a); 

here we have merely replaced the integral of a sum by the cor- 
responding sum of integrals, and have noticed that 

redx= e(b — a). 
_ 

As an indication of the importance of this theorem, we shall 
show that with its help we are able to integrate the function x°- for any 
irrational value of a, or, more exactly, to calculate the definite integral 

/x"- dx. Here we assume that < o < 6. 
_ 
We represent the index a as the limit of a sequence of rational numbers 
"l* a o^, . . . , so that a = lima„; here we can assume that none 

of the values a n is equal to — 1, since a itself is different from — 1. For 
the power a: a we then use the definition 

x"- = lim x a n 

and notice the following: no matter how small a positive number e we 
choose, we can always find an n so large that in the whole interval * 
i^igJwe have j x* — «"*» I < e. 

* This can be proved quite simply as follows. (Cf. Appendix I, « 3 n 69) 
Remembering that x°- is monotonic, and putting 8„ = a» - o, we have 

| a* - x*. | -a*|l-a*.|s(a» + 6a)(|l-a»»| + | 1 - W» | ); 
for a» lies between o". and 6«, so that a*» s a* + fta, a nd likewise 1 - a*, lies 
between 1 - <»s» and 1 - 68», so that |l-a&.|£(ll-aM + ll-M.l\ 
From Urn a*.- lim M. - 1, it follows that ' * ' * W * 1) - 

*» — >w n— >.<» 

lim | 1 - a*» | = lim II - 6*» I - 0; 

so if n is chosen large enough the right-hand side of the inequality is less than c 
This gives us I as*, -a* I < € simultaneously for all values of x in the interval 
a £ x £ 0. 



130 FUNDAMENTAL IDEAS [Chap. 

Now we need only apply the relationship mentioned above to the 
functions f(x) = x°- and g(x) = a;"*, obtaining 

rb sb pb 

— e(6 — a) + J x°™dx < / x a dx < I x°*dx + e(6 — a). 

J a Ja "a 

The integrals on the right and on the left, however, may be evaluated in 
accordance with the result on p. 85, giving 

— e(6 - a) H — (tr* +1 - W+ 1 ) 



< /V dx < — - (6«»+ 1 — o»«+ 1 ) + e(6 — a). 



If we now let the number s steadily decrease and tend to 0, the cor- 
responding values of n increase beyond all bounds; the numbers <x„, a"*, 
and &<"« must then converge to a, a a , and 6" respectively, and we immediately 
obtain the result 






x"- dx = (6«+ 1 — o^ 1 ). 

a + 1 



In other words, the integration formula that holds for rational values of a 
holds also for irrational values of a. 

From this it follows in virtue of the fundamental theorem of p. Ill 
that for positive values of x the differentiation formula 

d 

— x «+i = (a + 1)3° 

dx 

already obtained for rational values of a remains valid for irrational values 
of a also. 

Examples 

1. Find the intermediate value 5 of the mean value theorem of the 
integral calculus for the following, and interpret geometrically: 

xdx. 



(a) / Idx. (b) \ 

rb H 

(c) J x n dx. (d) / 

Ja Ja 



b dx 
x*' 



2. Let f(x) be continuous. Prove, from the mean value theorem of the 
integral calculus, that the derivative of the indefinite integral of f(x) is 
equal to f(x). 

3. (a) Evaluate l n = jx L l"dx. What is lim /„? Interpret geometri- 

cally. (6) Do the same for J n = j x n dx. 

Jo 



II] THE ESTIMATION OF INTEGRALS 131 

4.* Let the function /(£) be continuous for all values of 5, and let 
F(x) be denned by tie equation 

F(x) = i/* /(a: + t)dt ' 

where 8 is an arbitrary positive number. Prove that: 

(a) the function F(x) possesses a continuous derivative for all values 
of x; 

(6) in any fixed interval ogigi we can make | F{x) — j(x) \ < e, 
where e is an arbitrary pre-assigned positive number, by choosing 8 small 
enough. 

5.* Schivarz's inequality for integrals. 

Prove that for all continuous functions f(x), g(x) 

f (S^)fdxj\g(x)fdx ^ (f b f(x)g(x)dxy. 



Appendix to Chapter II 

1. The Existence of the Definite Integral of a 
Continuous Function 

We have still to give a proof of the fact that the definite 
integral of a continuous function between the limits a and b 
(a < b) always exists. For this purpose we recall the notation 
°f § 1 (P- 79), and consider the sum 

F n = i f(£ v )bx„. 

It is certainly true that 

£. = i f(v v )Ax v g F n 5S S /(«,) As„ = T n , 

v = 1 v =■ 1 

where f(v v ) denotes the least and/(w„) the greatest value of the 
function in the v-th sub-interval. The problem is to prove that 
F„ tends to a definite limit independent of the particular manner 
of subdivision and of the particular choice of the quantities £„, 
provided that as n increases the length of the longest sub-interval 
tends to zero. To establish this it is obviously necessary and 
sufficient to show that the two expressions F n and F~ n converge 
to one and the same limit. 



13a FUNDAMENTAL IDEAS [Chap 

No matter how small the positive number e is chosen, we 
know by the uniform continuity of f(x) that in every suffi- 
ciently small interval the "oscillation" | /(«„)— /(«„) | is 
less than e; so that if the subdivision is fine enough we cer- 
tainly must have 

^ T n - F» = i Ax r {f(u v ) -/(«,)} < e(6 - a). 

V ■= 1 

We therefore see that as n increases this difference must tend 
to zero, and so we can content ourselves with proving that one 
of the sums, say F„, converges. This convergence will be proved 
as soon as we show that | F n — F m | can be made as small as de- 
sired by requiring that the corresponding subdivisions (which 
we shall refer to as " subdivision n " and " subdivision m " 
respectively) go beyond a certain degree of fineness. This degree 
of fineness is characterized by the property that for both sub- 
divisions the oscillation of the function in each sub-interval is 
less than e (e > 0). We pass to a third subdivision whose points 
of division consist of all the points of subdivision n and of 
subdivision m taken together. This new subdivision, which has 
say I points of division, we denote by the suffix I, and we con- 
sider the corresponding upper sum Ft. We shall now estimate 
the value of \F n — F m \ by first obtaining estimates for the 
expressions \F~ n — F t \ and \F m — F t \. We assert that the 
following two relationships hold: 

F^T t ^T n and F^^It^F^. 

The proof follows at once from the meaning of our expressions. 
Let us consider say the v-th sub-interval of the subdivision n. 
This sub-interval will consist of one or several sub-intervals of 
the subdivision I; the terms corresponding to these intervals 
will each consist of two factors, one of which is a difference Ax 
and the other of which is certainly not greater than /(«„) and 
not less than /(»„). The sum of the lengths Ax of those intervals 
of the subdivision I which lie in the v-th sub-interval of the 
coarser subdivision n is, however, exactly Aa;„. Wo therefore 
see that the corresponding contribution to the sum F t must 
lie between the limits f(u y )Ax v aa.df(v v )Ax v . If we now sum over 
all the n sub-intervals we obtain the first of the above inequali- 



II] EXISTENCE OF DEFINITE INTEGRAL 133 

ties; the second is obtained in exactly the same way if we con- 
sider the subdivision m instead of the subdivision n. 

We have already seen that Y n — F\, < e(6 — a); it is like- 
wise true that F m — F^ < e(6 — a). From the inequalities for 
F t proved above, it therefore follows that 

0^T„-¥ l <e(b—a) and 0<, F^ t —¥ l < € (b- a). 

Thus it is also certain that 

I K- f^\ = I (FZ~F\)~ (F m - F\) I < 2e(6- a). 

Since e can be chosen as small as we please, this relation shows 
us by Cauchy's convergence test (p. 40) that the sequence 
of numbers F n actually converges. At the same time we see 
at once from our argument that the limiting value is completely 
independent of the manner of subdivision. 

The proof of the existence of the definite integral of a con- 
tinuous function is thus complete. 

Our method of proof teaches us still more. It shows us that 
in many cases we are also led to the integral by a somewhat 
more general limiting process. If, for example, /(a;) = 4>(x)r]t(x) 
and the interval from a to 6 is subdivided into n parts by the 
points of division x v , we consider instead of the sum £/(£,) Ax r 
the more general sum 

Z*(f/W(£,")Aav, 
where £/ and £„" are two not necessarily coincident points of 
the v-th sub-interval. This sum will also tend to the integral 



Jf(x)dx = J <f>(x)<Ji(x)dx 



as n increases, provided that the length of the longest sub-interval 
tends to zero. 

A corresponding statement holds for all sums formed in an 
analogous way; for example, the sum 

tends to the integral 

fv{<l>(x)* + 4>(x) 2 }dx. 



134 FUNDAMENTAL IDEAS [Chap. 

The proof of these facts follows lines exactly similar to the above 
and hence need not be worked out in detail. 



2. The Relation between the Mean Value Theorem op 
the Differential Calculus and the Mean Value 
Theorem of the Integral Calculus. 

Between the mean value theorem of the differential calculus 
and that of the integral calculus there exists a simple relation 
which is arrived at by way of the fundamental theorem (p. Ill) 
and which we give as an instructive example of the use of that 
theorem. We take the mean value theorem of the integral 
calculus in its more special form, 

ff(x)dx=(b-a)f(£). 

If we put ff(x)dx—F(x), so that f(x) = F'(x), the theorem 
just written takes the form 

F(b)- F(a)=(b-a)F'(t) 

b — a 

Here we can obviously choose for F(x) any function whose 
first derivative F'(x)=f(x) is continuous, and thus for such 
functions the mean value theorem of the differential calculus is 
proved. 

If we consider the more general form of the mean value 
theorem of the integral calculus, 

rf(x)p(x)dx=f(g) I p(x)dx, 

where p(x) is a function which in our interval is continuous and 
positive and f(x) is an arbitrary continuous function, we are 
led to a correspondingly more general mean value theorem of 
the differential calculus. We put 

Jf(x) p(x)dx = F(x), i.e. f(x)p (x) = F'(x), 
and fp(x)dx=G{x), i.e. p{x) = G'(x); 



II] THE MEAN VALUE THEOREMS 135 

the above mean value formula then takes the form 
F(b)-F(a) = {G(b)-G(a)}f(g), 

,, . Fix) 
or, since /(a;) = ^LJ 

F(b)-F(a) _F(j) 

0(6) -0(a) G'd)' 
where a =f= b. 

This formula, in which £ once again denotes a number inter- 
mediate between a and b, is called the generalized mean value 
theorem of the differential calculus. For this to be valid it is 
obviously sufficient to assume that F(x) and G{x) are continuous 
functions with continuous first derivatives and that in addition 
G'(x) is everywhere positive (or everywhere negative). For with 
these assumptions the whole process can be reversed. 

Finally, it should be observed that in the present discussion 
of the mean value theorem of the differential calculus we have 
had to make assumptions more stringent than the theorems in 
themselves require. (Cf. § 3, No. 8, p. 103, and later p. 203.) 

Example 

1. Show that if f(x) haa a continuous derivative in the interval 
* ^ x ^ b, then /(a) can be represented as the difference of two monotonia 
functions. 



CHAPTER III 

Differentiation and Integration of the 
Elementary Functions 

1. The Simplest Rules for Differentiation and 
their Applications 

In higher analysis and its applications it is usually the case 
that the problems of integration are more important than those 
of differentiation, but that differentiation offers less difficulty 
than integration. Consequently the natural method of building 
up the integral and differential calculus is first to learn to dif- 
ferentiate the widest possible classes of functions and then by 
virtue of the fundamental theorem (Chap. II, § 4, p. 116) to make 
the results thus obtained available for the solution of integration 
problems. In the following sections it will be our task to carry 
out this programme. To a certain extent we shall make a 
fresh start, since we shall work out the most important differen- 
tiations and integrations systematically without calling upon 
the results of last chapter. In this development of the subject 
certain rules for differentiation, with the first of which we are 
already acquainted (p. 96), will play an important part. 

1. Rules for Differentiation. 

We assume that in the interval which we are considering the 
functions f(x) and g (x) are differentiable; our rules then run as 
follows: 

Rule 1. Multiplication by a constant. 

If c is a constant and <f>(x) = cf{x), then <f>(x) is differentiable, 
and 

<f>\x) = cf'(x). 



Chap. Ill] RULES FOR DIFFERENTIATION 137 

This follows immediately from the relation 

4(x + h)-4( X ) /(» + *)-/(») 

A A 

if we take the limits as h -> 0. 
Rule 2. Derivative of a sum. 
If <ji{x) =f(x) + g(x), then <f>(x) is differentiable, and 

f (*)=/'(*) + flr'(a;); 

that is, the processes of differentiation and addition are inter- 
changeable. The same holds for the sum of any finite number (n) 
of terms 

#(*)=S /,(*), 
for which we obtain 

+'(z) = £/„'(*). 

We may pass over the proof, which after Chap. II, § 3 (p. 88) is 
fairly obvious. 

Rule 3. Derivative of a product. 

If <f>(x) = f(x)g(x), then <f>(x) is differentiable, and 

<l>'(x)=f(x)g'(x) + g(x)f'(x). 

The proof follows from the equation 

<f>(x+h)~<f,(x) __ f(x+h)g(x+h)-f(x)g(x) 
h h 

_ f^+h)g(x+h)-f{x+h)g(x)+f(x+h)g{x)-f{x)g(x) 

h 

= f(x+h) 9{x+h) -9W+g(x) f {x+h) -K X \ 
h h 

In this last expression the passage to the limit h -*■ can be 
directly carried out, yielding the formula stated. 

This formula takes a still more elegant form if we divide * 
throughout by <f>(x) = f{x)g{x). We then obtain 

$'{x) _f'{x) g'(x) 
4>(x) f{x) g(x)' 

* We most, of course, assume that 4>{x) is nowhere equal to zero. 



138 DIFFERENTIATION AND INTEGRATION [Chap. 

By repeated application of this product formula we obtain 
by induction for the derivative of a product of n factors an 
expression consisting of n terms, each of which consists of the 
derivative of one factor multiplied by all the other factors of 
the original product. In symbols: 

4>'(*) = ~{h(*)Ux)-..Ux)} 

or on division * by <J>(x) = Mx)f 2 (x) . . .f n (x) 

#*) /i(«) /,(*) /.(*) ,-ifJxj' 

Rule 4. Derivative of a quotient. 
For a quotient 

the following rule holds: the function <f>(x) is differentiable at 
every point at which g(x) does not vanish, and 

* u {9W 2 • 

If <f> (x) =j= 0, this can be written 

4>i x ) f(x) g{x)' 

If we accept the differentiability of <f>(x) as a hypothesis, we 
can apply the product rule to f(x) = <f>(x)g(x) and conclude that 

f'{x)^4>{x)g\x) + g{x) < j>'{x). 

By substituting-^ for tf>{x) on the right and solving for <f>'{x) 

we obtain the rule stated above. In order to prove the differen- 

* We most, of course, assume that <j>(x) is nowhere equal to zero. 



HI] RULES FOR DIFFERENTIATION 139 

tiability of <f>{x) as well as the rule we use the following method. 
We write 

/(»+*) f{x)_ 
4>(x+h)—<f>(x) _ g(x+h) g(x) 
h h 

jH /(*+A)-/(aQ _ 9(* + h)-g(x) 

=x » h 

g(x)g(x + h) 

If we now let h tend to 0, we arrive at the result stated; for by 
hypothesis the two terms obtained by performing the division 

on the right have definite limits, which are respectively ?WW 

AS'Wffr) rm- {SWY 

{q(x)\ 2 ' at ° nCe P roves botl1 tne existence of the limit 

on the left-hand side and the differentiation formula. 
2. Differentiation of the Rational Functions. 

To begin with, we shall again deduce the differentiation formula 

d 

— x n = na;" -1 

ax 

for every positive integer n, basing the proof on the rule for 
differentiating a product. We think of x n as a product of w 
factors, x n = x ... x, and thence obtain 



d 



.»-i : 



The second derivative of the function x» results if we use 
the above formula and the first rule of differentiation: 

d? 

— x n —n{n~ \)x n -\ 

Continuing the process, we obtain 
dx 3 



d? 

~x n =n(n—l)(n— 2)x nr ~ 3 



d n 

-3— x n = 1 . 2 . . . n = n! 

ax" 



i 4 o DIFFERENTIATION AND INTEGRATION [Chap. 

From the last of these it is clear that the (n+ l)-th derivative 
of x n vanishes everywhere. 

In virtue of our first two rules, a knowledge of the differ- 
entiation of powers at once enables us to differentiate any 
polynomial 

y = a + <H X + °» r? + • • • + a n x "- 

We have simply 

y' = ay + ^a^ + 3a 3 a? + • • • + na n x tt ~ 1 , 

and further 

y" = 2a 2 + 3 . 2a z x + 4 . Za^x 2 +... + «(«— l)a„a: B - 2 , 

and so on. 

The differentiation of any rational function now follows 
with the help of the quotient rule. In particular, we shall 
again deduce the differentiation formula for the function x n , 
where n = — m is a negative integer. The application of the 
quotient rule, together with the fact that the derivative of a 
constant is equal to zero, gives us the result 

mx™^ 1 m 



-(-) = 

dx vc"*/ 



j2m jpw»+l' 

or, if we take m = — n, 

d 

— x n = wa;" -1 , 

dx 

which agrees formally with the result for positive values of n 
and with the results given earlier (p. 95). 

3. Differentiation of the Trigonometric Functions. 

For the trigonometric functions sin a; and cos a; we have 
already (p. 96) obtained the differentiation formulae 

d . -,d 

— sina; = cosa; and — cosa; = — Binsr. 

dx dx 

The quotient rule now enables us to differentiate the functions 

sina; , . cosa; 

y = tana; = and y — cota; = — — . 

cosa; sin x 



Ill] RULES FOR DIFFERENTIATION i 4I 

According to the rale, the derivative of the first of these func- 
tions is 

. _ cos 2 a; + sin 2 a; 1 



cos 2 a; cos 2 a;' 

and we obtain the result 

<*.___ _1 
cos k a: 

Similarly, we obtain 



— tana; = —- J - = S ec 2 a; = 1 + tan 2 x. 



d „._ 1 



dx 



cota; = — -__ = — cosec 2 a! = —(1 + cot 2 a;). 



sin* a; 



2. The Corresponding Integral Formula 
1. General Boles for Integration. 

The fundamental theorem of p. 116 and the definition of the 
indefinite integral reveal to us the possibility of writing down 
an integral formula corresponding to each differentiation formula. 
The following rules of integration (of which the first two have 
already been mentioned oh p. 82) are completely equivalent to 
the first three rules of differentiation. 

Multiplication by a constant: If c is a constant, then 

fcf(x) dx = cff(x) dx. 

Integration of a sum: It is always true that 

/{/(*) + g(x)}dx =ff(x) dx+fg (x) dx. 

To the third rule of differentiation corresponds the rule for 
the integration of a product, or, as it is usually called, the rule 
for integration by parts. On integration the product rule gives 

j{f(*>)9(x)}'dx =Jf(x)g'(x)dx +fg(x)f'(x)dx. 

The indefinite integral on the left is obviously f(x)g(x) (except 
possibly for an additive constant), and we can therefore write 
the rule for integration by parts in the following form: 

Jf(x)9'(x)dx =f(x)g(x) -fg(x)f'(x)dx. 



142 DIFFERENTIATION AND INTEGRATION [Chap. 

This last integration, formula, the counterpart of the rule for 
the differentiation of a product, has been given here only for 
the sake of completeness; it will not become important for us 
until the next chapter (p. 218). 

2. Integration of the Simplest Functions. 

Corresponding to the differentiation formulae for special 
functions which we have recently found, we now set down the 
equivalent integration formulae. The formula 

d 



— x" = nx 



,n-l 



dx 
when expressed as an integration formula becomes 



/ 



x n ~ 1 dx = — , n 4= 0. 



For this formula merely means that the derivative of the right- 
hand side is equal to the expression under the integral sign 
on the left. If we replace n by n + 1, we obtain the integral 
formula 

fx n dx = x n+1 , n 4= — 1. 

J n-\- 1 

This formula holds for every integral index n (where n < 
it of course holds only if x 4= 0) with the exception of n = — 1, 
for which the denominator ft + 1 would vanish. Later (p. 167) 
this exceptional case will be studied in detail. 

The fundamental theorem of the integral calculus at once 
permits us to use our integral formulas for the determination of 
areas, that is, of definite integrals. By p. 117 we immediately 
obtain 



"'O 



x"dx = (b n + 1 — a n+1 ), »4=- 1, 

n -f- 1 

where if n is negative we assume that o and b are of the same 
sign, since otherwise the integrand would be discontinuous in 
the interval of integration. 

To the differentiation formulae for sin a;, cos a;, tana;, and cot a; 
correspond the following integration formulae: 



HI] RULES FOR INTEGRATION 143 

Jcoaxdx= sina:, fainxdx = — cosa;, 

/ — — dx = tana;, /"-— - dx = — cotx. 
J cos 2 a; ./ sin 2 a; 

From these formulae we obtain by way of the fundamental rule 
of Chap. II, § 4 (p. 117) the value of the definite integral between 
any limits, the only restriction being that when the last two 
formulas are used the interval of integration must not contain 
any point of discontinuity of the integrand. For example, 



r- 



coaxdx = sina; = sin& — sina. 



It scarcely needs to be emphasized that with the help of 
the first two rules of integration we are now in a position to 
integrate any polynomial in x, and, in fact, any linear combina- 
tion with arbitrary constant coefficients of the functions inte- 
grated here. The following point, however, should be noted. 
Rules of integration and rules of differentiation must according 
to the fundamental theorem be equivalent to one another; it 
is therefore possible first to prove the general integration rules 
of this section and then to read off the differentiation rules of 
the preceding section. The reader would be well advised to 
carry out this suggestion for himself. 

Examples 

1. Find the numerical values of all the derivatives of x s — x* at x = 1. 

2. What is the numerical value of the eleventh derivative of 

317a; 9 — 202a;' + 76 at x = 13J? 

3. Differentiate the following functions and write down the correspond- 
ing integral formulae: 

(a) ox+b. . aa? + 26a; + c 

(6) 25ca;'. «** + 2 P* + Y* 

1 1 



(c) + 2bx + cx\ if) j^^ j-j^j. 

(d) ax + b , . , (a?-V8a;« + 4)(s»+ VSx* + 4) 
cx + d Ky > *"+16 • 

4. Let P(x) = ffl + a x x + a^ + ... + a n x n . 
(a) Calculate the polynomial F(x) from the equation F(x) — F'(x) = P(x). 
(&)* Calculate F(x) from the equation c^x) + o^'ix) + c a F"(x) = P(x). 



144 DIFFERENTIATION AND INTEGRATION TChap. 

6. Differentiate the following functions and write down the corre- 
sponding integral formulae: 

(a) 2 sin x cos x. (c) x tan x. . . sin a ; 

... 1 .,. sin x + cos x x 

ifi) . (a) — 

1 + tan x sm x — cos x 

Recalling that sec x = , coseo x = , find the derivatives 

indicated in Ex. 6-9: ooax Bma: 

6. — sec x. 8. — coseo x. 
dx 3 dx* 

J* »4 

7. — seo x tan X. 9. ■— tan x sin x. 
tfct» dx* 

10. Find the limit as n -> 00 of the absolute value of the m-th deri- 
vative of — at the point x — 2. 

x 

Evaluate: 

11. yW + b)dx. 16. y(x* + A) dx. 

12. /"(ox" + 26x + c)dx. 16. /Ya cos x + -rrj dx - 

13. f(6x a +7x t +Sx*+3x t +l)dx. 17. f( 3a: + 7Bina: +^ _ ^)* ,: - 

14. /Yi + _ + — )dx. 18. F seo x tan x dx. 

3. The Inverse Function and its Derivative 

1. The General Formula for Differentiation. 

We have seen earlier (pp. 21 and 67) that a continuous func- 
tion y=f(x) has a continuous inverse in every interval in which 
it is monotonic. More exactly: 

If a ^ x ^ b is an interval in which the continuous function 
y = f (x) is monotonic, and if i (a) = a and f (b) = /?, then x is a 
function of y which in the interval between a and )S is one-valued, 
continuous, and monotonic. 

As we have already shown on p. 92, the concept of the deri- 
vative gives us a simple means for recognizing that a function is 
monotonic and therefore has an inverse. For a difEerentiable 
function is certainly always monotonic increasing if f'(x) is 
greater than zero throughout the corresponding interval, and 



HI] INVERSE FUNCTIONS i 4S 

similarly is monotonic decreasing if f'(x) is everywhere less than 
zero in the interval. 

We shall now prove the following theorem: 

// in the interval a < x < b the function y = f (x) is differen- 
tiable, and in that interval either f(x) > everywhere or eke 
i'(x) < everywhere, then the inverse function x = <f>(y) also 
possesses a derivative at every point of its interval of definition, 
and between the derivative of the given function y = f (x) and that 
of the inverse function x = (f>(y) there exists for corresponding 
values of x and y the relationship f'(x) . ^'(y) = 1, which we can 
also write in the form 

dx dx' 
dy 

In this last formula we again observe the flexibility 
of Leibnitz's notation. It is just as if the symbols dy 
and dx were quantities which could be operated with like 
actual numbers. The proof of this formula is correspondingly 
simple if we regard the derivative as the limit of the difference 
quotient, 

&y_ n m yx-y 



y'=f'(x)= lim =»= lim 



Ax- 



OASB Xt^-xXj^ — X 



where x and y=f(x), and x 1 and y 1 =f(x 1 ), respectively denote 
pairs of corresponding values. By hypothesis the first of these 
limiting values is not equal to zero. On account of the continuity 
°£ V —f( x ) an d x = j>(y) the equation lim Ax = is equivalent 
to lim Ay = 0, and consequently the relations y x ->■ y and x x ->- x 
are also equivalent. Therefore the limiting value 

lim*LZL5= fon^LZf 

*t->*yi — y y^yyi — y 

exists and is equal to — — v . On the other hand, the limiting value 

is by definition the derivative <f>'(y) of the inverse function <f)(y), 
and thus our formula is proved. 

This formula has a simple geometrical meaning, which is clearly shown 
in fig. 1. The tangent to the curve y = J(x) or x = <f(y) forms with the 

' (B798) 



146 DIFFERENTIATION AND INTEGRATION [Chap. 



positive x-axis an angle a, with the positive «/-axis an angle P, and from 
the geometrical meaning of the derivative 



y 




yC 



^1C 



f'(x) == tan a, <p'(y) = tan p. 

Since, however, the sum of the angles 
a and (3 is rc/2. tan a tan p = 1, and 
this relationship is exactly equivalent to 
our differentiation formula. 

We have hitherto expressly 
assumed that either f'(x) > or 
f'(x) < 0, i.e. that f'{x) is never 
zero. What, then, happens if 
/'(*)=(» If /» = every- 
where in an interval the function 
is constant there, and consequently has no inverse, since the 
same value of y must correspond to all values of x in the interval. 
If the equation f'(x) = is 
true only at isolated points, "' 

and if for the sake of sim- 
plicity f'(x) is assumed con- 
tinuous, then we must dis- 
tinguish whether on passing 
through these points f(x) 



Fig. i. — Differentiation of the 
inverse function 




o 

Fig. 2. — Parabola 




~? 



Fig. 3. — Cubical parabola 



changes sign or not. In the first case this point separates a point 
where the function is monotonic increasing from another where 
it is monotonic decreasing. In the neighbourhood of such a point 
there can be no single-valued inverse function. In the second 
case the vanishing of the derivative does not destroy the 
monotonic character of the function y=f(x), so that a single- 



HI] INVERSE FUNCTIONS 147 

valued inverse exists. But the inverse function will no longer 
be differentiable at the corresponding point; in fact, its derivative 
will be infinite there. The functions y=x 2 and y = a^ at the 
point x = offer examples of the two types. Figs. 2 and 3 
illustrate the behaviour of the two functions where they pass 
through the origin and at the same time show that one of the 
functions, namely y = as 8 , has a single-valued inverse, but that 
the other function, y = x% has not. 

2. The Inverse of the Power Function. 

The simplest example of an inverse function is offered by the 
functions y = x n for positive integers n and, as we at first assume, positive 
values of x. Under these conditions y 1 is always positive, so that for 
all positive values of y we can form a unique positive inverse function 

*= \/y=y 1,n - 

The derivative of this inverse function is immediately obtained in accor- 
dance with the above general rule by the following calculations: 

<% 1/w ) = dx = \_ = _J 1 1 = 1 1/n _ a 

dy dy dy nx"- 1 n y(«-D/» » y ' 

dx 

and if we now denote the independent variable by x, we may finally 
write 

dx dx n 

which agrees with the result obtained directly on p. 94. 

The point x = requires special consideration. If x approaches 
through positive values, dfaV^/dx, where n > 1, will obviously increase 
beyond all bounds; this corresponds to the fact that f or n > 1 the deri- 
vative of the n-th power f(x) = a;" vanishes at the origin. Geometrically 
this means that the curves y = a; 1 /", n > 1, touch the j/-axis at the origin 
(cf. fig. 17, p. 34). 

For the sake of completeness it should be noted that for odd values of n 
the assumption that x > can be omitted and the function y=x n can be 
considered for all values of x without loss of its monotonic character or of 

the uniqueness of its inverse. The differentiation formula — (w 1 '") = - » l '" —1 

dy n 

d(x n ) 
still holds for negative values of y; for x = 0, n > 1, we have — — = 0, 

dx 

which corresponds to an infinite derivative (dx/dy) of the inverse function 

at the point y =»= 0. 



148 DIFFERENTIATION AND INTEGRATION [Chap. 

3. The Inverse Trigonometric Functions. 

In order to form the inverses of the trigonometric functions 
we once again consider the graphs of sin a;, cos a;, tana;, and cot a;. 
We at once see from figs. 14 and 15, p. 25, that for each of these 
functions it is necessary to select a definite interval if we are 
to speak of a unique inverse; , for the lines y = c parallel to the 
x-axis cut the curves in an infinite number of points, if at all. 



■ sinx 




X-arcsiny 



Fig. 4. — The inverse sine function 



For the function y = sin a; the derivative y' = cos a; will e.g. 
be positive in the interval — n-/2 < x < it/2. In this interval 
the sine accordingly has an inverse function; we write the in- 
verse function of the sine in the form * 

x = arc sin^ 

(read arc sine y; this means the angle whose sine has the value y). 
This function runs monotonically from — tt/2 to +7r/2 as y tra- 
verses the interval — 1 to +1. If we especially wish to emphasize 
that we are considering the inverse function of the sine for this 
very interval, we speak of the principal value of the arc sine. 
If we form the inverse function for some other interval in which 
sina; is monotonic, e.g. the interval +tt/2 < x < 3tt/2, we 
obtain " another branch " of the arc sine; without the exact 
statement of the interval in which the values of the function 
must lie the arc sine is a multiple-valued function, and in fact 
has an infinite number of values. 

In general, the fact that arc siny is multiple- valued is 
expressed by the statement that to any one value y of the sine 
there corresponds not only the angle x but also the angle 
2kir + x, as well as the angle (2k + l)ir — x, where k is any 
integer (cf. fig. 4). 

* The notation x = waT'y is also used in English books. 



Ill] 



INVERSE FUNCTIONS 



149 



The differentiation of the function x = arc siny is performed 
in virtue of our general rule by the following short calcula- 
tion: 



dx 
dy 



1_ 
V' 



1 

cos a; 



± V(l - sin 2 a;) + V(l - V 2 )' 



where the square root is to be taken as positive if we confine 
ourselves to the first interval mentioned.* 

If the independent variable is finally changed back from 
y to x, the differentiation formula for the function arc sin a: is 
obtained in the following form: 

d 1 

— arc smx = — — -. 

dx V(l — a; 2 ) 

Here it is assumed that the arc sine lies between — w/2 and +w/2, 
and the square root sign is chosen positive. 



Ly-cosx 




x-arccosy 



Fig. 5. — The inverse cosine function 



For the inverse function of y= cos a;, denoted by arc cos z, 
we obtain the differentiation formula 

d 1 

— arc cosa; = — 

dx v(l 



x 2 ) 



in exactly the same way. Here we take the positive sign of the 
root if the value of arc cos a; is taken in the interval between 
and tr (not, as in the case of arc sinx, between — tt/2 and +w/2); 
cf. fig. 5. 

A word remains to be said about the end-points x = — 1 and 
x= +1. The derivatives become infinite on approaching these 
end-points, corresponding to the fact that the graphs of the 

» If instead of this we had chosen the interval w/2 < x < 3ir/2, correspond- 
ing to the substitution of x + it for *, we Bhould have had to use the negative 
square root, since coax is negative in this interval. 



150 DIFFERENTIATION AND INTEGRATION [Chap. 

inverse sine and inverse cosine must possess vertical tangents at 
these points. 

We can deal with the inverse functions of the tangent and 
cotangent in an analogous way. The function y = tan x, whose de- 
rivative 1 /cos 2 a; for x 4= n-/2 -f- /for 
is everywhere positive, has a 
unique inverse in the interval 
— ir/2 < x < it 12. We call this 
inverse function x = arc tan y 
or (by interchange of the letters 
x and y)y= arc tan x. We see at 
once from fig. 6 that the original 
many-valuedness of the inverse 
— i.e. the many-valuedness which 
occurs if the interval of the 
values of the function is not 
fixed — is expressed by the fact 
that for each x we could have 
chosen instead of y any of the 
values y -\-1cit (where k is an 
integer). For the function y = cota; the inverse x = arc coty, or 
(by interchange of x and y) y = arc cot a;, is uniquely determined 
if we require that its value shall lie in the interval from to tr; 
the many-valuedness of arc cot a; is otherwise the same as for 
arc tan a;. 

The differentiation formulae may be found as follows: 

dx 1 li 
x = arc tany, — = _ = cos 2 a; = = _ • 

dy dy 1 -f tan a 3 1 + y*' 

dx 

. dx . . 1 1 

x = arc cotw, — = — sm 2 a; = — = _ x . 

dy 1 + cot 2 a; 1 -f y*' 

or finally, if we denote the independent variable by x, 

d . 1 

— arc tana; = — , 

dx 1 + x* 




Fig. 6. — The inverse tangent function 



d 1 

— - arc cota; = — . 

dx l-\-x* 



HI] INVERSE FUNCTIONS 151 

4. The Corresponding Integral Formula. 

Expressed in the language of the indefinite integral, the 
formulae which we have just derived read as follows: 

J -. , » dx = arc tanas, J dx = —arc cotsc. 

Between the pair of formulae on the left and that on the right, 
which express each indefinite integral in the form of two functions 
which appear entirely different, no contradiction exists. We 
must remember that in the case of the indefinite integral an 
arbitrary additive constant remains at our disposal. If we choose 
these constants so that they differ by tt/2 and recall that 
it/2 — arc cos a; = arc sin a; and likewise w/2 — arc cot a; = arc tana: 
this formal disagreement is immediately cleared up. The in- 
definiteness simply depends on the fact that the indefinite 
integral is not a single definite function, but a whole family of 
functions which differ from one another by arbitrary additive 
constants. The equation for an indefinite integral specifies not 
the value, but only o value, of it. As we have already remarked, 
it would be more correct to express this fact by always including 
the undetermined constant, thus writing, not 

ff(x)dx=F(x), 
but ff(x)dx=F(x) + c 

For convenience, however, it is usual to avoid this more detailed 
form; the reader should therefore be all the more careful to bear 
in mind the indefiniteness which is always associated with the 
shorter form (see also p. 116). 

From the formulae for indefinite integration there immedi- 
ately follow formulae for definite integration, as on p. 117. 
In particular, 



r 



dx 

■ = arc tana: 



1 + a* 



= arc tan 6 — arc tana. 



i5« DIFFERENTIATION AND INTEGRATION [Chap. 



If we put a = 0, b = 1 and recall that tanO = and tanir/4 = I, 
we obtain the remarkable formula 



tt_ r 1 1 
4 Jo 1 + 



4-z 2 



dx. 



The number it, which originally arose from the consideration 
of the circle, is by this formula brought into a very simple relation- 




ship with the rational function 
defined as shown in fig. 7. 



Fig. 7. — ir/2 illustrated by an area 
1 



\ + X 



, and is expressed by the area 



Examples 

x* dy 

1. If « = — , y = 16 corresponds to x = 8. Find — for x = 8; solve 

a; 3 * dx 

u = — for x and find — for y = 16, and show that the values of these 
a 4 dy 

derivatives are consistent with the rule for inverse functions. 



2. Prove that (a) arc sin oc+ arc sin p = arc sin (a V 1 — p 2 -f- P V 1 — a 2 ); 
(6)arc since + arc sin(3=arc cos(Vl— a 2 Vl — p 2 — aP); 

a+P 



(c) arc tan a + arc tan P = arc tan 



1-aG 



Differentiate the expressions in Ex. 3-10 and write down the corre- 
sponding integral formulae: 






6. 



\/x 



1 — tana; 



9. 



arc sini 
arc tan a: 



4. Va 



7. arc sinar.aro oosa;. 10. B arc cotse -f- 



1 + Vx 



8. 



1 + arc tana; 
1 — arc tana; 



Ill] INVERSE FUNCTIONS r S3 

II. Using graph paper, plot y = on a large scale. By oounting 

' — — 5 dx, thus obtaining an estimate for - (of. Ex 1 
F . x*x,. o 1 + & 4 • ' 

4. Differentiation of a Function of a Function 

1. The Chain Rule. 

The preceding rules for differentiation enable us to differen- 
tiate every function which can be expressed as a rational expres- 
sion whose terms are functions with known derivatives. We 
can, however, take yet another important step forward and 
differentiate all those functions obtained by compounding func- 
tions with known derivatives. Let <f>(x) be a function which is 
differentiable in an interval a^Lx^b and assumes all values 
in the interval a^<f>^ /?. We now wish to consider a second 
differentiable function g(<f>) of the independent variable <j>, in 
which the variable <f> ranges over the interval from a to /?. We 
can now regard the function g(<j>) = g{<f>(x)} =f(x) as a function 
of a; in the interval a^.x<Lb. The function f(x) = g{<f>(x)} 
will then be called a function of x compounded from the 
functions g and <f>, or a function of a function. 

If, for example, <p(x) = 1 — x* and gr(<p) = V<p, this compound func- 
tion is simply f(x) = V(l — a; 2 ). For the interval ogigJwe here take 
the interval ^ x ^ 1. The values of the function <j>(x) exactly fill up the 
interval ^ ip g 1; the compound function f(x) = V(l — x 2 ) is there- 
fore denned in the interval ^ x ^ 1. 

Another example of the compounding of functions is the function 
f(x) — V(l +X 2 }, where the compounding process may be indicated by 
the equations 

y(x)=l + x*, g( 9 ) = V9 

and where the value of the function <p(ar) runs through all positive 
numbers ^ 1, so that the function f(x) = g{<?(x)} can be formed for all 
values of x. 

In compounding functions in this way we must naturally be careful 
to restrict ourselves to intervals a gas^i for which the compound 
function is defined. For example, the compound function V(l — x 2 ) is 
defined only for values of a; in the region -lgj;^l, and not in the 
region 1 < x ^ 2, for when a; is in this last interval the values of the 
function tp(x) consist of negative numbers, for which the function g(<f) is 
not defined. 

Just as we can compound two functions with one another, we can and 

• • (B798) 



154 DIFFERENTIATION AND INTEGRATION [Chap. 

must consider functions in which the compounding process is performed 
more than once. Such a function is 

V (1 + aro tan a?) 
which can be built up by the compounding process 



<p(x) = x*, <\>(<p) = 1 + aro tan <p, g(ty) = V<K<p) = f(x). 

For the differentiation of compound functions we have the 
following fundamental theorem, the chain rule of the differential 
calculus: 

The function f(x) — g{<^(x)} is differentiable, and its derivative 
is given by the equation 

or, in Leibnitz's notation, 

dy _dy d<j> 
dx d<f> dx' 

In words: the derivative of the compound function is the product 
of the derivatives of the constituent functions. 

The proof of this formula follows very easily if we recall the 
meaning of the derivative. For any arbitrary Ace =)= and cor- 
responding values of A<f> and Ag there exist two quantities e 
and 7], tending to with Ax, such that 

&9 = 9'(<! > )&<l> + «A<£ an d A<£ = <f>'(x)Ax + tjAx; 

we have only to calculate ij from the second equation and, where 
A<f> =j= 0, e from the first equation, while if A<f> = 0, we put e = 0. 
If in the first of these equations we now substitute the value of 
Acj) from the second equation, we obtain 

A<7 = 9'{<t>)4>'{x)Ax + {rf(4>) + ef (x) + erj) Ax, 

or jf = *W(*) + {r,g'(<f>) + ef (*) + «,}. 

In this equation, however, we can let Ace tend to 0, and at once 
obtain the result stated, since the bracket on the right tends to 
zero with Ax. Consequently the left-hand side of our equation 
has a limit f'(x), and this limit is equal to the first term on the 
right-hand side, as was stated.* 

* We could also have proved the rule by carrying out the passage to the 

limit As -*■ 0, and consequently A<j> -*• 0, in the equation =£ — QL . ^r. The 

Ax A# Ax 



Ill] FUNCTIONS OF A FUNCTION 155 

By successive application of our formula we can immediately 
extend it to functions which arise from the compounding of more 
than two functions. If, for example, 

y = g(u), u = <f>(v), v = if,{x), 

we can think of y=f(x) as a function of x\ its derivative is 
given by the rule 

ax du dv ax 

The case of a function compounded of an arbitrary number of 
functions is essentially similar. The proof may be left to the reader. 

2. Examples. 

As a very simple example we consider the function y—nf-, where we 
put a = p/q, q being a positive integer and p a positive or negative integer, 
so that a is an arbitrary positive or negative rational number. Let x be 
positive. By the chain rule with 

y = 9*, 9 = x l 'i 
we have the formula 

y' = pqp-l . I a;(l-9)/« _ P x v lt~ 1 , 
? 9 

so that for arbitrary rational values of a we obtain the differentiation 
formula j 

— x a = cue" -1 , 

dx 

in agreement with the result already found in another way in Chap. II, 
§ 3 (p. 94). 

As a second example, we consider 

y=V(l — a?) or y=V<f, 

where 9 = 1 — x 2 and — 1 < x < 1. The chain rule gives us 

j,'= _L .(_2z) = - x 



2V9 V(l — x 2 )' 

Further examples are given in the following brief calculations: 
1. y = arc sin V(l — x 2 ), 

dy = 1 dV(l — x*) 

dx V{1 — (1-x 2 )}' dx 

= _L ~ x ~ =c * 

~° \x\'y/(l-x*) "Wa-a?)' 



method in the text is, however, to be preferred, since it avoids the necessity 
for considering the case <j>'(x) — specially. 



156 DIFFERENTIATION AND INTEGRATION [Chap. 
dy 1 \\ — x/ 

B=2 V(K)' * 

= V(l - x) 2 1 

= 2 V(l + *)'(!- a;) 2 (1 + *) 1/2 (1 - s) 3/2 ' 



The chain rule for differentiation can also be expressed in the form of 
an integration formula, in agreement with the fact that to each differen- 
tiation formula there corresponds a completely equivalent integration 
formula. Nevertheless, we will pass over this formula for the present, 
since we have no immediate need of it here and, moreover, it is discussed 
in detail later (Chap. IV, § 2, p. 207). 

3. Further Remarks on the Integration and Differentiation of 
x a when a is Irrational. 
In view of the elementary definition of the power x" by the equation 
s" = lim x Tn , 

where the numbers r n form a sequence of rational numbers with the limit a, 
we might be tempted to effect the differentiation of x°- by direct passage 
to the limit in the differentiation formula 



dx 



x " = r n x ' 



We are not entitled to do this unless we have the right to conclude that 

d d 

from the relation x r * -»■ x* there follows the relation — x n -> jt x*. There 

is, however, a very serious objection 
to such a passage to the limit. For 
in any arbitrarily small neighbour- 
hood of a given curve other curves 
may be drawn whose direction at 
arbitrarily selected points differs 
from the direction of the original 

— „ . . „. . . . . ,. curve by any desired amount; for 

Fig. 8. — Approximation to a straight line , 

by wavy curves example, we may approximate to 

a straight line by a wave lying ar- 
bitrarily near it, the angle between the wave and the line reaching a 
value as high as 45° (see fig. 8). In other words, the above example 
shows us that from the fact that two functions differ only very little from 
one another, we cannot immediately conclude that their derivatives also are 
everywhere nearly equal to one another. This objection forbids us to 



Ill] FUNCTIONS OF A FUNCTION 157 

perform the apparently obvious passage to the limit, in the absence of 
further justification. 

In this respect, however, the integral behaves quite differently from 
the derivative. We have already observed on p. 128 that if two functions 
differ by less than e throughout the interval from o to 6, their integrals 
must differ by less than e(6 — a). We there used this result to establish 
the validity of the differentiation formula 

x a + 1 = x*. 



a. + 1 dx 

or, replacing a + 1 by a, 

d 

— x* = ax" -1 . 

dx 

In this indirect way, therefore, the relation — x r n -* — a;" given above 
is verified. " ,x " ,x 

The above discussion is a characteristic example of the interrelations 
of the differential calculus and the integral calculus. Yet in principle it 
is preferable to replace (as we shall do on p. 173 et seq.) the elementary 
definition of *" by another, essentially simpler, definition which will lead 
us once more to the same result, and this time directly. 

Examples 
Differentiate the following functions: 

1. (x + l) s . 11. sin (a; 2 ). 

2. (3a; + 6)*. 12. V(l + sin"*). 

3. (x» - 3x* - x 3 ) 1 . 1 

13. a^sin-L 

4. —L-. ** 

1 + s ,. . 1 + a: 

14. tan — ' — . 
1 1-a: 



1 — ** 15. sin(a: 2 + 3a; + 2). 

6. (ax + b) n (ra an integer). 16. arc sin (3 + x 3 ). 

7. 17. arc sin (cos a;). 

3-l V(a^— 1) 

v ' 18. sin (arc cos V(l — a; 2 )). 

c l/ax* + bx+c\ ,\ 

8 -yl W + mx+ n } 19. *'»_.-*». 

9. ( V(l - x) 2/3 ) 5 . 20. [sin (a; + 7) ] ^*. 

10. sin 2 a;. 21. [arc sin (a cos a; + b) ]". 



158 DIFFERENTIATION AND INTEGRATION [Chap. 

5. Maxima and Minima 

Now that we have attained a certain mastery of the problem 
of differentiating the elementary functions and the functions 
compounded from them, we are in a position to make a variety 
of applications. Here we shall consider the simplest of these 
applications, the theory of maxima and minima of a function, 
in conjunction with a geometrical discussion of the second deri- 
vative, and then in the next section we shall again take up the 
thread of the general theory. 

1. Convexity or Concavity of Curves. 



By definition the derivative j~f(x) of a function /(x) gives 

dx 

the slope of the curve y =/(%)■ This slope can itself be repre- 



y, 


/ 1 
/ 1 







/ X 


*x 




Fig. ga.— /"(*) > 



Fie. gb.~ r(x) < 



sented by a curve y = — f(x) = f'(x), the derived curve of 

dx 

the given curve. The slope of this last curve will be given by the 

d d? 

derivative —f'(x) = —-f(x)=f"(x), the second derivative of 
dx dx 2 

f(x), and so on. If the second derivative f"(x) is positive at a 
point x — so that owing to continuity (which we here assume) it 
is positive in a certain neighbourhood of the point x— then the 
derivative /'(x) must increase as it passes this point in the direc- 
tion of increasing values of x. Hence the curve y = f(x) turns 
its convex side towards the direction of decreasing values of y. 
The opposite is true if f"(x) is negative. In the first case, there- 



Ill] 



MAXIMA AND MINIMA 



»59 



fore, the curve in the neighbourhood of the point lies above the 

tangent, in the second case below the tangent (see figs. 9a and b). 

Special consideration is required only in the case of points 

where f"(x) = 0. On passing through such a point the second 



IV 




Fig. 10. — Point of inflection 



-5 



derivative f"(x) will, as a rule, change its sign. Such a point will 
then be a point of transition between the two cases indicated 
above; that is, the tangent will on one side be above the curve, 
and on the other side below it, so that besides touching the 
curve it will also cross it (see fig. 10). Such a point is called a 
paint of inflection of the curve, and the corresponding tangent 
is called an inflectional tangent. 

The simplest example is given by the function y — x*, the cubical 
parabola, for which the ai-axis itself is an inflectional tangent at the point 
x = 0. Another example is given by the function j(x) = sin x, for which 
/'(«) = d(sinx)/dx= cos x and f"(x)~d*(smx)/dx>=—Bmx. Conse- 
quently /'(0) = 1 and /"(0) = 0; since the sign of f"(x) changes at x = 0, 
the sine curve has at the origin an inflectional tangent inclined at an 
angle of 45° to the s-axis. 

It must, however, be noted that points can exist where f"(x) = 
although the tangent does not cut the curve, but remains entirely on one 
side of it. For example, the curve y «*= aj* lies entirely above the z-axis, 
although the second derivative f"{x) vanishes for x = 0. 

2. Maxima and Minima. 

We say that a continuous function or a curve y = f(x) has a 
maximum (minimum) at a point £ if in at least some neighbour- 
hood of the point x = £ the values of the function /(x) for x 4= £ 
are all less than/(£) (greater than /(£)), By a neighbourhood of 
a point we mean an interval o 5S x ^ /3 which contains the 



160 DIFFERENTIATION AND INTEGRATION [Chap. 

point £ in its interior. Geometrically speaking, such maxima 
and minima are respectively the wave-crests and wave-troughs of 
the curve. A glance at fig. 11 shows us that the value of the 

maximum at one point P s 

may very well be less than 

the value of the minimum 

\ at another point; P 2 ; thus 

\^^-t4 the concept of maximum 

I | and minimum is always to 

x some extent relative, on 
Fig. it.— Maxima and minima account of the restriction to 

a certain neighbourhood. 
If we wish to fix upon the actual greatest or least value of 
the function we must employ special means for deciding how 
this value is to be selected from among the maxima or minima. 
The point for us at present is to find the (relative) maxima 
or minima, or, to use a word that covers both maxima and 
ininima, the relative extreme values (extrema) * of a given func- 
tion or curve. This problem, which is very frequently en- 
countered in geometry, mechanics, and physics and which occurs 
in many other applications, formed one of the principal incentives 
for the development of the differential and integral calculus in 
the seventeenth century. 

We see at once that if the function is assumed to be differen- 
tiable, the tangent to the curve at an extreme value £ must be 
horizontal. Hence the condition 

/'(£) = 

is a necessary condition for an extreme value; by solving this 
equation for the unknown f we obtain the points at which an 
extreme value may possibly occur. Our condition, however, is 
by no means a sufficient condition for an extreme value; there 
may be points at which the derivative vanishes, i.e. at which 
the tangent is horizontal, although the curve has neither a maxi- 
mum nor a minimum there. This occurs if at the given point 
the curve has a horizontal inflectional tangent cutting it, as in 
the above example of the function y = x 3 at the point x = 0. 

* The expressions turning value, turning point, are also used. On the other 
hand, the terms stationary value, stationary point, include inflections as well as 
maxima and minima. 



in J MAXIMA AND MINIMA 161 

If, however, we have found a point at which f'(x) vanishes, 
we may immediately conclude that the function has a maximum 
at that point if /"(£) < 0, a minimum if/"(f) > 0. For in the 
first case the curve in the neighbourhood of this point lies com- 
pletely below the tangent, in the second case completely above 
the tangent. 

Instead of basing the deduction of our necessary condition 
on intuition we could, of course, have given an easy proof by ( 
purely analytical methods (cf. the exactly analogous considera- 
tions for Rolle's theorem, p. 105). If the function f{x) has a 
maximum at the point £, then for all sufficiently small values of 
h different from the expression /(f) -/(£ + h) must be posi- 
tive. Therefore the quotient ?~^ ( ^ will be positive or 

negative, according as A is negative or positive. Thus if h tends 
to zero through negative values the limit of this quotient cannot 
be negative, while if h tends to zero through positive values the 
limit cannot be positive. But since we have assumed that the 
derivative exists these two limits must be equal to one another 
and, in fact, to /'(£), which therefore can only have the value 
zero; we must have f'(£) = 0. A similar proof holds for the case 
of a mi nimum 

We can also formulate, and prove analytically, conditions 
which are necessary and sufficient for the occurrence of a maximum 
or a minimum, without involving the second derivative. We 
suppose that the function /(x) is continuous and has a continuous 
derivative f'(x) which vanishes only at a finite number of 
points. 

Then f (x) has a maximum or a minimum at the point x = gif, 
and only if, the derivative f'(x) changes sign on passing through 
this point; in particular, the function has a minimum if the deri- 
vative is negative to the left of £ and positive to the right, while in 
the contrary case it has a maximum. 

We prove this by using the mean value theorem. First, we 
observe that to the left and right of £ there exist intervals 
f i < x < £ and £ <x<£ 2 (extending to the nearest points 
at which f'(x) = 0) in each of which f'(x) has only one sign. If 
the signs of f'(x) in these two intervals are different, then 
f(f + A) — /(f) = A/'(f + 0h) has the same sign for all numeri- 
cally small values of h, whether h is positive or negative, so that 



162 DIFFERENTIATION AND INTEGRATION [Chap. 

/(£) is an extreme value. Iif'(x) has the same sign in both in- 
tervals, then A/'(| + 6h) changes sign when A does, so that 
/(!+ A) is greater than/(|) on one side and less than/(£) on 
the other side, and there is no extreme value. Our theorem is 
thus proved. 

At the same time we see that the value f(i) is the greatest 
or least value of the function in every interval, containing the 
point f , in which the only change of sign of f'(x) occurs at 
| itself. 

The mean value theorem on which this proof is based can 
still be used even if f(x) is not differentiable at an end-point 
of the interval in which it is applied, provided that f(x) 
is differentiable at all the other points of the interval; for 
example, the above proof still holds if fix) does not exist 
at x = f . This leads us to the following more general result: 
if the function /(x) is continuous in an interval containing the 
point $, and everywhere in this interval, with the possible 
exception of | itself, has a derivative /'(a;) which vanishes at not 
more than a finite number of points, then/(x) has an extreme 
value at the point x = £ if, and only if, the point g separates 
two intervals in which f'(x) has different signs. For example, 
the function y = | x | has a minimum at x = 0, since y' > 
for x > and y' < for x < (cf. fig. 9, p. 97). The function 
y = tyx* likewise has a minimum at the point x = 0, even 
though its derivative § ar* is infinite there (cf. fig. 12, p. 99). 

In addition we make the following remark on the general 
theory of maxima and minima: the finding of maxima and 
minima, is not directly equivalent to the finding of the greatest 
and least values of a function in a closed interval. In the case 
of a monotonic function these greatest and least values will be 
assumed at the ends of the interval and are therefore not maxima 
and minima in our sense; for this latter ooncept refers to a 
complete neighbourhood of the place in question. Thus for ex- 
ample the function f(x) == x in the interval <£ x <| 1 assumes 
its greatest value at the point x s= 1, and its least value at x = 0, 
and a corresponding statement holds for every monotonic func- 
tion. The function y = arc tan x, whose derivative is 1/(1 + x % ), 
is monotonic for — oo < x < +» , and in that open interval 
possesses neither a maximum nor a minimum, nor a greatest 
or a least value. 



in J MAXIMA AND MINIMA ^63 

If after finding the zeros of f\x) we wish to make sure that 
we have thereby found the points at which the function has its 
greatest or least values, we can often make use of the following 
criterion: 

A point i at which f(x) vanishes gives the least or greatest 
value of the function f(x) in a whole interval, if throughout that 
interval i"(x) > or f"(x) < respectively. 

For if I and £ + h both belong to the interval 

f'tf + h) =/'(£ + h) -/'(£) ^ hf"(g + eh), 

by the mean value theorem. Hence at the point x = $ + h the 
derivative/'^) has the same sign as h or the opposite sign, accord- 
ing as/"(x) > oxf"(x) < 0; the statement then follows from 
the remark following the theorem at the top of p. 162. 

3. Examples 01 Maxima and Minima. 

Ex. 1. Of all rectangles of given area, to find that with the least peri- 

Let a* be the area of the rectangle and x the length of one side (here 
we must cons l der x as ranging over the interval < x < «,); then the 
length of the other side is a a /*, and half the perimeter is given by 

/(*) = *+?!. 
x 

We have f(x) = 1 - * /"(*) = 2o_ a . 

The equation /'(?) «, has the single positive root I = a. For this value 
/ (x) is positive (as it is for any positive value of x); it therefore gives the 
required least value, and we obtain the very plausible result that of all 
rectangles of given area the square has the smallest perimeter. 

Ex. 2. Of all triangles with given base and given area, to find that 
with the least perimeter. 

To solve this problem, we take the *-axis along the given base AB 
and the middle point of AB as the origin. If C is the vertex of the triangle, 
ft its altitude (which is fixed), and (x, ft) are the co-ordinates of the vertex, 
then the sum of the two sides of the triangle AG and BG which are to be 
determined will be given by 

f(x) = V{(z + a)" + ft")} + V{(x - a)* + ft*} 
where 2a is the length of the base. From this we obtain 

V{(* + a) 2 + h>] ^V{( X - o)» + ft*}' 



164 



DIFFERENTIATION AND INTEGRATION [Chap. 

-(x+af 1 , -(x-af 



V{(* + a) 2 + A 2 } 3 
1 



+ 



V{(x + a)* + h*} + V{(x - a) 2 + A 2 } 3 



+ 



V{(x- 
A 2 



-a) 2 + A 2 } 

-. + ■ 



A 2 



V {{x + af + ft 2 } 8 V {(x - af + A 2 } 8 

We see at once (1) that /'(0) vanishes, (2) that f"(x) is always positive; 
hence at x = there is a least value. For since f"(x) > the first 
derivative f'(x) always increases and therefore cannot be equal to zero 
at any other point, so that the point x = must really give the least 
value of /(*). This least value is accordingly given by the isosceles triangle. 
Similarly, we find that of all triangles with given perimeter and given 

base the isosceles triangle has 
the greatest area. 

Ex. 3. To find a point on 
a given straight line such that 
the sum of its distances from 
two given fixed points is a 
minimum. 

Let there be given a straight 
line and two fixed points A 
and B on the same side of the 
line. We wish to find a point 
P on the straight line such 
that the distance PA + PB 
has the least possible value. 
We take the given line as the x-axis and use the notation of fig. 12. 
Then the distance in question is given by 

f(x)*= V(x* + A 2 ) + V{(x - a) 2 + h x *}, 
and we obtain 

t'(x\ = X 4- a—a 

' V ' vV-f A 2 ) V{(x - af + A! 2 }' 

—3? , 1 , -(x—af 




Fig. 1 a. — Law of reflection 



/"(*) = 



y/(3? + A 2 ) 3 
+ 



+ 



V(x* + A 2 ) 
1 



+ 



V^x-af + h^f 



A 2 



V{(x~- 



if + A x 2 } 
A, 2 



VV + A 2 ) 3 V{(a; - o) 2 + A x 2 } 3 ' 

The equation/' (?) = accordingly gives us 

I _ _ a-l 

V{(5-a) 2 +A, 2 }* 



or 



V(5 2 + A 2 ) ' 

cosa= cosp, 



Ill] 



MAXIMA AND MINIMA 



i65 



which means that the two lines PA and PB must form equal angles 
with the given line. The positive sign of f"(x) shows us that we really 
have a least value. 

The solution of this prohlem is olosely connected with the optical law 
of reflection. By an important principle of optics, known as Fermat's 
principle of least time, the path of a light ray is determined by the property 
that the time that the light takes to go from a point A to a point B under 
known conditions must be the least possible. If the condition is imposed 
that a ray of light shall on its way from A to B pass through some point 
on a given straight line (say on a mirror), we see that the shortest time 
will be taken along the ray for which the " angle of incidence " is equal 
to the " angle of reflection ". 

Ex. 4. The Law of Refraction.— -Let there be given two points A and 
B on opposite sides of the s-axis. Which path from A to B corresponds to 
the shortest possible time if the velocity on one side of the z-axis is c, 
and on the other side c 2 ? 




Fig. 13. — Law of refraction 

It is clear that this shortest path must lie along two portions of straight 
lines meeting one another at a point P on the z-axis. Using the notation 
of fig. 13, we obtain the two expressions V(A a + x*) and V{A,» + (o — x) 1 } 
for the lengths PA, PB respectively, and we find the time of passage along 
this path by dividing the lengths of the two segments by the corresponding 
velocities and adding. This gives us 

f(x) = 1 V(h* + x*) + I V {V + (a - *)*}, 

for the time taken. 

By differentiation, we obtain 






a— x 



c, V(#» + x») c 8 V {V + (a - x)*}' 
1 A« .1 A,' 



, + i 



c, V(A* + x»)» ^ c 2 V{V + (<* -*)*}»' 
As we readily see from the figure, the equation f'(x) = 0, i.e. 



e, V(A" + *») e, V {V + (a - *)» }' 



166 DIFFERENTIATION AND INTEGRATION [Chap. 

is equivalent to the condition — sin a = — sin (3, or 

sin a Cj 
sin P c 2 

We leave it to the reader to prove that there is only one point which 
satisfies this condition and that this point actually yields the required 
least value. The physical meanii-g of our example is again given by 
the optical principle of least time. A ray of light travelling between two 
points describes the path of shortest time. If c, and c 2 are the velocities of 
light on either side of the boundary of two optical media, the path of the 
light will be that given by our result, which accordingly gives Snell's law 
of refraction. 

Examples 

1. Find the maxima, minima, and points of inflection of the following 
functions. Graph them, and determine the regions of increase and de- 
crease, and of convexity and concavity: 

(a) a* — 6x + 2. (6) s 2/3 (l - x). (o) Zcftl + a 2 ). 
(d) x s /(x i + 1). (e) sin 2 *. 

2. Determine the maxima, minima, and points of inflection of 
a? + $P X + ?• Discuss the nature of the roots of a? -f- Zpx + q = 0. 

3. Which point of the hyperbola y 2 — %x* = 1 is nearest to the 
point x = 0, y = 3? 

4. Let P be a fixed point with co-ordinates x , y in the first quadrant 
of a rectangular co-ordinate system. Find the equation of the line through 
P such that the length intercepted between the axes is a minimum. 

5. A statue 12 ft. high stands on a pillar 15 ft. high. At what distance 
must a man 6 ft. high stand in order that the statue may subtend the 
greatest possible angle at his eye? 

6. Two sources of light, of intensities a and 6, are at a distance d apart. 
At which point of the line joining them is the illumination least? (Assume 
that the illumination is proportional to the intensity and inversely pro- 
portional to the square of the distance.) 

7. Of all rectangles with a given area, find 

(a) the one with the smallest perimeter; 
(6) the one with the shortest diagonal. 

x* v 2 

8. In the ellipse - — (- — = 1 inscribe the rectangle of greatest area. 

o ! 6 2 

9. Two sides of a triangle are a and 6. Determine the third side so that 
the area is a maximum. 

10. A circle of radius r is divided into two segments by a line g at a 
distance h from the centre. In the smaller of these segments inscribe the 
rectangle of greatest possible area. 

11. Of all circular cylinders with a given volume, find the one with the 
least area. 



Ill] MAXIMA AND MINIMA 167 

12. Given the parabola y a = 2px, p > 0, and a point P(x = £, y = -n) 
within it (r? < 2p5), find the shortest path (consisting of two line seg- 
ments) leading from P to a point Q on the parabola and then to the focus 
F{x = \p,y = 0) of the parabola. Show that the angle FQP is bisected 
by the normal to the parabola, and that QP is parallel to the axis of the 
parabola. (Principle of the parabolic mirror.) 

13.* A prism deflects a beam of light travelling in a plane perpendicular 
to the edge of the prism. What must the relative position of prism and 
beam be for the deflection to be a minimum? 

14. Given n fixed numbers a lt . . . , a n , determine x so that S (a t — x)» 
is a minimum. < -1 

15. Prove that if p > 1 and x > 0, x* — 1 |> p(x — 1). 

16. Prove the inequality 1 ^ 5E? S - , ^ x <, n 

x 71 2 

17. Prove that (a) tana: §i,0gj^-. 

* 2 

(0) cosa: ;> 1 — — . 
- 2 

18.* Given Oj > 0, a 2 > o„ > 0, determine the minimum of 

at + ■ . . + <!„_! + z 



-V^a^ . . . a n _,x 
for * > 0. Use the result to prove by mathematical induction that 

1 + . . . + o. 



V^OiO, . 



«i 



6. The Logarithm and the Exponential Function 

The systematic relations between the differential calculus 
and the integral calculus lead naturally to a convenient method 
of approach to the exponential function and the logarithm. 
Although we have already (pp. 25, 69) investigated these 
functions, we now define them afresh and develop their theory 
again without making any use of our previous definition and 
the results based on it. We begin with the logarithm, and then 
obtain the exponential function as its inverse. 

1. Definition of the Logarithm. The Differentiation Formula. 

We have seen that indefinite integration of the power x n 
for integral indices n in general leads to a power of x. The 
only exception is the function 1/x, which does not appear as the 



168 DIFFERENTIATION AND INTEGRATION [Chap. 

derivative of any of the functions which we have dealt 
with so far. It is natural to suppose that the indefinite 
integral of the function 1/x represents a new sort of function; 
so, following up this idea, we will proceed to investigate the 
function 

for x > 0. We call it the logarithm of x, or, more accurately, the 

natural logarithm of x, and write it y — log a; or y = nat log a;. 

We have denoted the variable of integration by £ in order to 

avoid confusion with the upper limit <c. 

The choice of the number 1 as lower limit is an arbitrary one, 

which, however, will soon prove its convenience. 

In the course of the following argument it will appear that 

the logarithm denned here is the same as the logarithm which we 

previously (p. 70) denned in an 
"elementary way". But, as we 
once more emphasize, the results 
of the following investigations are 
independent of those obtained 
earlier. 

Geometrically our logarithmic func- 
tion means the area shown shaded 
Fig. 14. — Log* illustrated by an area in fig. 14, which is bounded above by 

the rectangular hyperbola y = 1/5, 
below by the £-axis, and at the sides by the lines 5=1 and % = x. This 
area is to be reckoned positive if x > 1, negative if x < 1. For x = 1 the 
area vanishes, and we therefore have log 1 = 0. 

According to the above definition the derivative of the 
logarithm is given by the formula 

d(logx) _ 1 
dx x 

Here let us expressly emphasize that we assume through- 
out that the argument x is positive; the logarithm of or 
of any negative value cannot be formed in accordance with 
the formula above, for the integrand 1/f becomes infinite 
when f = 0. On the other hand, if we choose some negative 
number, say —1, for the lower limit, we can form the integral 




ill] LOGARITHM AND EXPONENTIAL FUNCTION 169 

with a negative upper limit x, i.e. we can consider the expres- 
sion 



r*dj 



(x < 0). 



Owing to the significance of the integral as the limit of a sum or 
as an area, we see that for x < 

f*d£ r-*d£ rMdg . . , 

In conformity with this we can in general write the formula for 
indefinite integration as 

/dx 
— = log I X [. 

The logarithm can, of course, 
be represented by means of a 
graph. This graph, the loga- 
rithmio curve, is shown in fig. 
15. We have already seen (p. 
119 et seq.) how to construct it. 

2. The Addition Theorem. 

The logarithm defined as 
above obeys the following 
fundamental law: 

log (oft) = log a + log 6. 



yj 




1 1 







/I 2 


3 * 


X 



Fig. 15 



The proof of this addition theorem follows directly from the 
differentiation formula. For, writing z = log (ax), and applying 
the chain rule, we have 



dz 1 1 

_ = _.a=-. 
dx ax x 



But 



d , 1 

te logx== x' 



and since the functions z and logx have the same derivative 
they differ only by a constant, so that 2 = log a; -f cor 

log ox = log* + c. 



170 DIFFERENTIATION AND INTEGRATION [Chap. 

This being true for all positive values of x, we first put x = 1 to 
find c; since logl = 0, this yields 

log a = c. 

Substituting this value for c, we have 

log ax = log a; + loga, 
whence, for x=b, 

logab = logos + log&, 

which was to be proved. 

For arbitrary positive numbers o^ o 2 , . . . , a n the equation 

logKa 2 . . • o n ) = logo! + loga 2 + . . . -f logo„ 

follows from the addition theorem for the logarithm. 

In particular, if all the numbers a l5 a 2 , . . . , a„ are equal to 
one and the same number a, we have 

loga" = n logo. 
Similarly, it follows that 

logo + log- = logl = 0, 
a 

so that logo = — log -. 

a 

If, further, we put \/a = a it follows that logo = n log a, or 

log-y/a = logo 1 '" = - logo. 
n 

From this by repeated use of the addition theorem we find 
that, when m is a positive integer, 

- logo = log a/o™ = logo™'". 
n 

The equation logo r = r logo 

is thus proved for all positive rational values of r , and for r = 
it is obviously correct. For negative rational values of r it is 
also valid, for then 

logo r = log-—- = — logo -r = r logo. 



Ill] LOGARITHM AND EXPONENTIAL FUNCTION 171 

3. Monotonic Character and Values of the Logarithm. 

The value of the logarithm obviously increases when x in- 
creases, and decreases when x decreases; the logarithm is there- 
fore a monotonic function. 

Since the derivative 1/x becomes smaller and smaller as x 
increases, the function increases more and more slowly as x 
increases. Nevertheless, as x increases beyond all bounds the 
function log a: does not tend to a positive limit, but becomes 
infinite; that is to say, for every positive number A, no matter 
how large, there are values of x for which logs > A. This fact 
follows very readily from the addition theorem. For log 2" == 
rc log2, and since log 2 is a positive number, by taking x = 2" 
with sufficiently large values of n we can make logo; as large 
as we please. 

Since log(l/2«) = — n log 2, we see that as x tends to zero 
through positive values loga: is negative and increases numeri- 
cally beyond all bounds. 

Summing up these results: 

The function loga; is a monotonic function which assumes 
all values between -00 and +00 as the independent variable x 
ranges over the oontinuum of positive numbers. 

4. The Inverse Function of the Logarithm (the Exponential 
Function). 

Since the function y = loga; (x > 0) is a monotonic function 
of x which assumes all real values, its inverse function, which we 
shall at first denote by x = E(y), must be a single-valued mono- 
tome function denned for every real value of y; it is difEerentiable, 
since loga; itself is differentiable. We interchange the notation 
for the dependent and independent variables, and proceed to 
study the function E(x) in detail. In the first place, it must 
clearly be positive for every value of x. Further, we must have 

E(0)=1; 

for this equation is equivalent to the statement that log 1 = 0. 
Secondly, from the addition theorem for the logarithm there 
immediately follows the multiplication theorem 

E(a)E(p)=E(a+p). 



172 DIFFERENTIATION AND INTEGRATION [Chap. 

To prove this we need only notice that the equations 
E{a) = a, E(P)=b, E{a+P) = c 

are equivalent to 

o = loga, /? = logfc, a + fi = logc. 

Since by the addition theorem for the logarithm a + j3 = logafc, 
it must be true that c = ab, which proves the multiplication 
theorem. 

From this theorem we derive a fundamental property of the 
function y = E(x), which gives us the right to call our function 
the exponential function and to write it symbolically in the form 

y=e*. 

In order to obtain this property we observe that there must 
be a number — which we shall call * e — for which 

loge = 1. 

This is equivalent to the definition 

E(l) = e. 

Using the multiplication theorem for the function E(x), we have 

E(n) = e n , 

and, in the same way, for positive integers m and n, 

*(?) = ** 

which we could also have found directly from the addition 
theorem for the logarithm. 

The equation E(r) = e r thus proved for positive rational 
numbers r holds also for negative rational numbers in virtue of 
the equation 

E{r)E(—r) = E(0) = 1. 

The function E{x) is therefore a function which is continuous 
for all values of x, and which for rational values of x coincides 
with e x . These facts give us the right to call our function e" for 

* Its identity with the number e considered on p. 43 will be proved in No. 6 
(p. 175). 



Ill] LOGARITHM AND EXPONENTIAL FUNCTION 173 

arbitrary irrational values of x also.* (It should be noticed that 
here the continuity of e* is an immediate consequence of its 
definition as the inverse function of a continuous monotonic 
function, while if the elementary definition is adopted the con- 
tinuity must be proved.) 

The exponential function is differentiated according to the 
formula 

d „* * 

— e" = e* or y = y. 

This formula expresses the important fact that the derivative of 
the exponential function is the 
function itself. 

The proof is extremely 
simple. For we have x = logy, 
whence, by the formula for the 
differentiation of the loga- 



rithm, we have — = -, 
dy y 



and 



then by the rule for inverse 
functions 



dy 
dx 



y=e*, 




as was stated. 



Fig. 16. — The exponential function 



The graph of the exponential function &, the so-called exponential 
curve, is obtained by reflection of the logarithmic curve in the line which 
bisects the first quadrant. It is shown in fig. 16. 

5. The General Exponential Function a" and the General 
Power x". 

The exponential function a" for an arbitrary positive base a 
is now simply defined by the equation 

y=a*= e* l08a , 

* If we anticipate the fact, which will be proved on p. 175, that our number e 
is identical with the number so denoted previously, we have now proved that the 
definition given here yields the same exponential function with base « as was 
formerly defined by the process of raising to powers. For, according to that 
elementary definition, we defined the values of e x for irrational z's as the limit 
of the expressions e*n, where x n takes on a sequence of rational values with the 
limit x. 



174 DIFFERENTIATION AND INTEGRATION [Chap 

which agrees with the earlier definition in virtue of the 
relation 

e loga ==a. 

Using the chain rule we immediately obtain 

— a* = — e* loga = e* 1<>Ba . loga, 
dx dx 

= a" loga. 

The inverse function of the exponential function y = a" is 
called the logarithm to the base a and is written 

x=log a y, 

while the logarithmic function previously introduced, when a 
distinction is necessary, is spoken of as the natural logarithm, 
or logarithm to the base e. 

From the definition it follows immediately that 

logy = x loga = log a i/ . loga, 

which shows us that the logarithm of y to an arbitrary positive 
base a 4= 1 is obtained by multiplying the natural logarithm of 
y by the reciprocal of the natural logarithm of a, the modulus 
of the system of logarithms to the base * a. 

Instead of our previous definition of the general power 
x*(x > 0) we shall now define this power by the equation 

x* =e° log *. 

The rule for differentiating the power af follows immediately 
from the definition, using the chain rule; for 

Lx°- = e alosx .-=ax a - 1 , 
dx x 

in agreement with our previous result (cf. p. 155). 

* If we take = 10 we obtain the ordinary " Briggian " logarithms, which 
have already been met with in elementary mathematics and which are advan- 
tageous for use in numerical calculations. 



Ill] LOGARITHM AND EXPONENTIAL FUNCTION 175 

6. The Exponential Function and the Logarithm represented 
as Limits. 

We are now in a position to state important limiting relations 
referring to the quantities introduced above. We begin with the 
formula for differentiating the function f(x) = log 3, 

-=/'(*)= k™ /<* + *> -/(*) - 1^ l°g(« + ft)-log» 
x a-^o A A _^ h 

= limllog(l + ^). 

A->Oft \ X/ 

If we put - = 2, this becomes 
x 

lim - log(l + zh) = 2 . 

A->qA 

Since the function ef is continuous for all values of x, this implies 
that 

e*=Iime' ,0 ^+*WA'=li m (l + ^)i/A > . # (o) 

If in particular we give h the sequence of values 1, -, -, , , ., I, . . ., 
we have 2 3 n 



lim 



( 1 + B = e " W 



If to z we assign the value 1, formula (a) gives the following 
important fact: 

As h tends to zero, the expression (1 + h) 1/h tends to the 
number e: 

lim (1 + hj Llh = e. 

A->0 

Formula (6) gives 

lim (l + *Y = e, 

which proves that the number e is the same as the number 
denoted by the symbol e on p. 43. 

From the differentiation formula for a x , 

a x log a = lim — ~» 

*->q h 



176 DIFFERENTIATION AND INTEGRATION [Chap. 

it follows for x = that 

i ,. «» - 1 

loga = iim — - — > 
a-*-o h 

a formula which expresses the logarithm of a directly as a 
limit. 

To this equation we append the remark that by its means 
we can complete the relation 

[" x «dx = -i— (6* +1 -a* +1 ) 

J a a + 1 

established earlier. We have always been obliged to exclude 
the case a = — 1. Now, however, we can trace what happens 
when the number a tends to the limit —1. If we put a= 1 
the left-hand side will by our definition of the logarithm have 
the limit * 



t 



dx , , 
— = log 6; 
1 x 



the right-hand side therefore has the same limit when o -»• — 1. 
This fact, moreover, is in accordance with the formula 

b h — 1 
log6=hm— _— ; 
A-»o n 

we need only write a + 1 = h. 

We have thus cleared up the exceptional case a = — 1 in 
the integration formula which we have so often used. The 
formula above is still meaningless when a = — 1, but as a limit 
formula it retains its significance as a -> — 1. 

7. Final Remarks. 

Here we briefly review the train of thought followed out in 
this section. We first defined the natural logarithm y = loga; 
for x > by means of an integral, whence we immediately 
deduced the differentiation formula, the addition theorem, and 
the existence of an inverse. We then investigated the inverse 
function y = ^", where the number e was seen to be the number 

* We have here carried out the passage to the limit a — »• — 1 under the 
integral sign without further investigation; cf. the discussion on p. 128 et seq. 



Ill] LOGARITHM AND EXPONENTIAL FUNCTION 177 

whose logarithm is 1, and we derived its differentiation formula, 
as well as limit expressions for it and for the logarithm. The 
introduction of the functions y = of = e" log * and y=a x =e x lo « a 
followed naturally. 

In the discussion given here, as contrasted with the " elemen- 
tary " treatment, the question of continuity causes no difficulty, 
since the logarithm is defined as an integral and therefore as a 
continuous and differentiable function, whose inverse function 
is also continuous. 

Examples 

1. Sketch the function y = - (1 ^ x ^2) on a large scale, using 

x 

graph paper, and find log, 2 by counting squares. 
Differentiate the functions in Ex. 2-6: 

2. x(logx — 1). 4. log{x + V(l + x 2 )}. 

3. log logx. 5. log{ V(l + logx) — sinx). 

i/(x 2 + 1) 

6. Differentiate log — y — — -; (a) by using the chain rule and the 

V (2 + x) 
quotient rule, without preliminary simplification; (6) first simplifying 
by means of the theorems on logarithms. 

7. (a) Differentiate y = , ^^ + 1} 

V(x-2)V(x*+l) 

(b) Differentiate the same function, first taking logarithms and sim- 
plifying. 

/ x\ n 

8.* Given lim s„ = 0, prove that lim ( 1 + e„ . - 1 =1. 
n— >-«> n— >«A W' 

9. Show that the function y = er aX (a cosx-|- 6 sinx) satisfies the 
equation 

y" + 2<xy' + (a a + l)y=0 

for all values of a and 6. 

10.* Show that — («- 1 ' x *) = P "J a,) e - 1/l ', when x =t= 0, where PJx) is 

dx n x 3 " 

a polynomial of degree 2n — 2. Establish the " recurrence formula " 
P n+ A*) = (2 - 3nx*) P n (x) + x»P n '(x). 

11. Find the maximum of y — x\ a e~ **, where X and a are constants. 
Find the locus of this maximum when X is allowed to vary. 

12. Differentiate aM (a > 0). 

13. Differentiate a****™*'. 

7 1*798) 



178 DIFFERENTIATION AND INTEGRATION [Chap. 

7. Some Applications of the Exponential Function 

In this section we shall consider some miscellaneous problems 
involving the exponential function, and we shall thus gain an 
insight into the fundamental importance of this function in all 
sorts of applications. 

1. Definition of the Exponential Function by Means of a Dif- 
ferential Equation. 

We can define the exponential function by a simple theorem, 
whose use will save us many detailed investigations of particular 
cases. 

If a function y = f (x) satisfies an equation of the form 

y'=ay 
where a is a constant other than zero, then y has the form 
y=f(x) = ce**, 

where c is also a constant; and conversely, every function of the form 
ce°* satisfies the equation y' = ay. The latter is usually briefly 
referred to as a differential equation, since it expresses a relation 
between the function and its derivative. 

In order to make the theorem clear, we notice first of all 
that in the simplest case a = 1 the above equation becomes 
y' = y. We know that y=e x satisfies this equation, and it is 
clear that the same is also true of y = ce x , if c is an arbitrary 
constant. Conversely, we can easily see that no other function 
satisfies the differential equation. For if y is such a function, we 
consider the function u = ye~*. We must then have 

u' = y'e~* — ye'" = e-%' — y). 

But the right-hand side vanishes, since we have assumed that 
y' = y; hence u' = 0, so that by p. 114 et seq. u is a constant 
c and y = ce x , as we wished to prove. 

The case of any non-zero value of a can be treated in exactly 
the same way as the special case a = 1. If we introduce the 
function u = ye~°*, we obtain the equation u' = y'e~° x — aye~"*- 
Hence from the assumed differential equation we find that 
u' = 0, so that « = c and y = ce°*. The converse is clear. 



Ill] THE EXPONENTIAL FUNCTION 179 

We will now apply this theorem to a number of examples 
and thus make it more intelligible. 

2. Interest Compounded Continuously. Radioactive Disintegra- 
tion. 

A capital sum, or principal, which has its interest added to it at 
regular periods of time, increases by jumps at these interest periods in 
the following manner. If 100a is the rate of interest per cent, and if further 
the interest accrued is added to the principal at the end of each year, 
then after x years the accumulated amount of an original principal of 1 
will be 

(1 + a)«. 

If, however, the principal had the interest added to it not at the end 
of each year, but at the end of each »-th part of a year, then after x years 
the principal would amount to 



R)' 



Taking x = 1 for the sake of simplicity, i.e. reckoning the interest at 
100a per cent for one year, we find that if the interest is computed in this 
latter way the principal I amounts after one year to 



(-!)"■ 



If we now let n increase beyond all bounds, i.e. if we let the interest be 
calculated at shorter and shorter intervals, the limiting case will signify 
in a sense that the interest is compounded continuously, at each instant; 
and we see that the total amount after one year will be e a times the original 
principal. Similarly, if the interest is calculated in this manner, an original 
principal of 1 will have grown after x years to an amount e"*; here x may 
be any number, integral or otherwise. 

The discussion in No. 1 (p. 178) forms a framework within which 
examples of this type are readily understood. We consider a quantity, 
given by the number y, which increases (or decreases) with the time. 
Let the rate at which this quantity increases or decreases be proportional 
to the total quantity. Then if we take the time as the independent variable 
x, we obtain a law of the form y' = ay for the rate of increase, where a, 
the factor of proportionality, is positive or negative according as the 
quantity is increasing or decreasing. Then in accordance with No. 1 the 
quantity y itself will be given by a formula 

y = ce« x , 

where the meaning of the constant is immediately obvious if we con- 
sider the instant x = 0. At that instant e"* = 1, and we find that c = y 
is the quantity at the beginning of the time considered, so that we may 
write 



180 DIFFERENTIATION AND INTEGRATION [Chap. 

A characteristic example of the use of these ideas is the case of radio- 
active disintegration. The rate at which the total quantity y of the radio- 
active substance is diminishing at any instant is proportional to the total 
quantity present at tha* instant; this is a priori plausible, as each portion 
of the substance decreases as rapidly as every other portion. Therefore 
the quantity y of the substance expressed as a function of the time satis- 
fies a relation of the form y" = — ky, where k is to be taken as positive 
since we are dealing with a diminishing quantity. The quantity of sub- 
stance is thus expressed as a function of the time by y = y e~ ka , where y 
is the amount of the substance at the beginning of the time considered 
(time x = 0). 

After a certain time t the radioactive substance will have diminished 
to half its original quantity. This so-called half-value period is given by 
the equation to. = ifor*. 

log 2 
whence we immediately obtain t = -f— . 

k 

3. Cooling or Heating of a Body by a Surrounding Medium. 

Another typical example of the occurrence of the exponential function 
is offered by the cooling of a body, e.g. a metal plate, which is immersed in 
a very large bath of given temperature. In considering this cooling we 
assume that the surrounding bath is so large that its temperature ia un- 
affected by the cooling process. We further assume that at each instant 
all parts of the immersed body are at the same temperature, and that the 
rate at which the temperature changes is proportional to the difference 
between the temperature of the body and that of the surrounding 
medium (Newton's law of cooling). 

If we denote the time by x and the temperature difference by y = y(x), 
this law of cooling is expressed by the equation 

y' = — ley, 

where k is a positive constant whose value depends on the body itself. 
From this instantaneous relationship, which expresses the effect of the 
cooling process at a given instant, we now wish to derive an " integral 
law " which will allow us to find the temperature at an arbitrary time x 
from the temperature at an initial time x = 0. The theorem of No. 1 
(p. 178) immediately gives us this integral law in the form 

y = ce _fel! , 

where k is the above-mentioned constant depending on the body. This 
shows that the temperature decreases " exponentially " and tends to 
become equal to the external temperature. The rapidity with which this 
happens is expressed by the number k. As before, we find the meaning 
of the constant c by considering the instant x = 0; this gives us y a = e, 
so that our law of cooling can finally be written in the form 

y = y^r hx . 



Ill] THE EXPONENTIAL FUNCTION 181 

It is obvious that the same discussion will also apply to the heating 
of a body. The only difference is that the initial difference of temperature 
y„ is in this case negative instead of positive. 

4. Variation of the Atmospheric Pressure with the Height above 
the Surface of the Earth. 

As a further example of the occurrence of the exponential formula we 
shall deduce the law according to which the atmospheric pressure varies 
with height. We here make use (1) of the physical fact that the atmospheric 
pressure is equal to the weight of the column of air vertically above a 
surface of area 1, and (2) of Boyle's law, according to which the pressure 
of the air (p) at a given constant temperature is proportional to the density 
of the air (a). Boyle's law, expressed in symbols, is p = aa, where a is a 
constant which depends on a specific physical property of the air and in 
addition is proportional to the absolute temperature — here we are not 
concerned with this, as we shall assume that the temperature is constant. 
Our problem is to determine p = /(A) as a function of the height (A) above 
the surface of the earth. 

If by p we denote the atmospheric pressure at the surface of the earth, 

i.e. the total weight of the air column supported by a unit area, and by 

a (X) the density of the air at the height X above the earth, the weight of the 

f* 
column up to the height h will be given by the integral / a(X)<2X. The 

pressure at height h will therefore be ° 

p = f(h) = p - [ o(X)iX. 
Jo 

By differentiation this yields the following relation between the pressure 
p = f(h) and the density <j(h): 

°(A) = -/W = -¥'■ 

We now use Boyle's law to eliminate the quantity a from this equation, 

thus obtaining an equation 

1 
p'= — -p 
a 

which involves the unknown pressure function only. From p. 178 it follows 
that 

V = /(*) = ce _A/a . 

If as above we denote the pressure at the earth's surface, i.e. /(0), by p w 
it follows immediately that o = p , and consequently 

p = f(h) = j» e-*/«. 

Changing to logarithms, we obtain 

A=alog?' . 
P 



i8a DIFFERENTIATION AND INTEGRATION [Chap. 

These two formulae find frequent application. For example, if the oonstant 
a is known they enable us to find the height of a place from the barometric 
pressure, or to find the difference in height of two places by measuring the 
atmospheric pressure at each place. Again, if the atmospheric pressure 
and the height h are known we can determine the constant a, which is of 
great importance in gas theory. 

5. Advance of a Chemical Reaction. 

We now consider an example from chemistry, namely, the so-called 
unimolecidar reaction. We suppose that a substance is dissolved in a rela- 
tively large amount of solvent, say a quantity of cane sugar in water. If a 
chemical reaction takes place, the chemical law of mass action in this 
simple case states that the rate of reaction is proportional to the quantity 
of reacting substance present. If we suppose that the cane sugar is being 
transformed by catalytic action into invert sugar, and if by u(x) we denote 
the quantity of cane sugar which at time x is still unchanged, the velocity 
of reaction will be — du/dx, and in accordance with the law of mass action 
an equation of the form 

du , 

-- = — ku 
Ax 

holds, where k is a constant depending on the substance reacting. From 
this instantaneous law we immediately obtain, as on p. 178, an integral 
law, which gives us the amount of cane sugar as a function of the time: 

u(x) = ae~ kx . 

This formula clearly shows us how the chemical reaction tends asymptoti- 
cally to its final state u = 0, that is, complete transformation of the re- 
acting substance. The constant a is obviously the quantity present at 
time x = 0. 

6. Making and Breaking an Electric Circuit. 

As a final example we consider the growth of a (direct) electric current 
when a circuit is completed (or its decay when the circuit is broken). If 
R is the resistance of the circuit and E the impressed electromotive force 
(voltage), the current / will gradually increase from its original value 
to the steady final value E/JR. We have therefore to consider / as a func- 
tion of the time. The growth of the ourrent depends on the self-induction 
of the circuit; the circuit has a characteristic constant L, the coefficient 
of self-induction, of such a nature that as the ourrent increases an electro- 
motive force of magnitude Ldljdx, opposed to the external electromotive 
force E, is developed. From Ohm's law, according to which the product 
of the resistance and the current is at each instant equal to the actual 
effeotive voltage, we obtain the relation 

IR=E-L A 1. 
ax 



Ill] THE EXPONENTIAL FUNCTION 183 

Here we put 

we immediately find that f'(x) w — -- f(x), so that by the theorem 

Li 

on p. 178 /(a;) = /(0)e-**/£ Recalling that 2(0) = 0, we see that 

/(0) «i — — , and thus we obtain the expression 
it 

'-/(*) + §- fa -•-**> 

for the current as a function of the time. 

IVom this expression we see that when the circuit is closed the current 
tends asymptotically to its steady value E/B. 

Examples 

1. The function f(x) satisfies the equation 

/(* + 2/) =/(*)/&). 
(o) If f(x) is differentiable, either f(x) = or else /(a;) = e°*. 
(6)* If f(x) is continuous, either /(*) s or else f(x) = e". 

2. If a differentiable function f(x) satisfies the equation 

then f(x) = a logs. 

3. A quantity of radium weighs 1 gm. at time t = 0. At time t = 10 
(years) it has diminished to -997 gm. After what time will it have diminished 
to -5 gm.? 

4. Solve the following differential equations: 

(a) y' = a(y — 0). (e) y' — a y = p«« 
(6) y' — a.y— p. (d) y' _ ay = p e i*. 

8. The Hyperbolic Functions 
1. Analytical Definition. 

In many applications the exponential function does not enter 
alone, but in combinations of the form 

l(e» + <r«) or |(e*-<r«). 

It is convenient to introduce these and similar combinations as 
special functions; we denote them as follows: 



184 DIFFERENTIATION AND INTEGRATION [Chap. 



sinha; = 



cosh a: = 



e x _|_ e -x 



tanha;: 



e x -\- e~ x ' 



cotha: = 



e x + er» 



and we call them the hyperbolic sine, hyperbolic cosine, hyper- 
bolic tangent, and hyperbolic cotan- 
gent respectively. The functions 
sinha;, cosh a;, and tanha; are de- 
fined for all values of x, while in 
the case of cotha; the point x = 
must be excluded. This notation 
is designed to express a certain 
analogy with the trigonometric 
functions; it is this analogy, which 
we are about to study in detail, 
that justifies special consideration 
of our new functions. In figs. 17, 
18, and 19 the graphs of the hy- 
perbolic functions are shown; the 
dotted lines in fig. 17 are the 
graphs of y = \e x and y = \e~ x , 

from which the graphs of sinha; and cosh a; may easily be 

constructed. 




Fig. 17 




Fig. 1 8 



We see that cosh a; is an even function, i.e. a function which 
remains unchanged when x is replaced by — x, while sinha; is an 
odd function, i.e. a function that changes sign when x is replaced 
by -x. (Cf. p. 20.) 



Ill] 



THE HYPERBOLIC FUNCTIONS 



185 



The function 



cosha; = ! 

2 



v-coth: 



-2 



X 



is, by its definition, positive for all values of x. It has its least 
value when x = 0; coshO = 1. 

Between cosh a; and sinha; there exists the fundamental re- 
lation 

cosh 2 a; — sinh 2 a; = 1, 

which follows immediately 
from the definitions of these 
functions. If we now denote 
the independent variable by t 
instead of x and write 

x = cosh*, y = sinhf, 

we have 

x 2 — f = 1; 

that is, the point with the co- 
ordinates x = cosht, y = waht 
moves along the rectangular 
hyperbola x 2 — y 2 = 1 as t 
runs through the whole scale 
of values from — 00 to +00. 
According to the defining equation, x ^ 1, and we may easily con- 
vince ourselves that y runs through the whole scale of values — 00 
to + co as t does; for if t tends to infinity so does e', while e~* tends 
to zero. We may therefore state more exactly that as t runs from 
— 00 to +00 , the equations x = cosh(, y = sinhtf give us one 
branch, namely, the right-hand one, of the rectangular hyperbola. 

2. Addition Theorems and Formulae for Differentiation. 

From the definitions of our functions there follow the formulae, 
known as addition theorems: 

cosh (a -f 6) = cosha cosh 6 -f sinha sinh&, 
sinh(a + b) = sinha coshft + cosha sinh&. 

The proofs are obtained at once if we write 
e°e* + e~"e~ h 



Fig. 19 



cosh (oft): 

7» 



-, sinh(a + 6): 



e°e» 



e~ a e~ 



2 

(1798) 



186 DIFFERENTIATION AND INTEGRATION [Chap. 

and in these equations put 

e° = cosha -f- sinha, e~" = cosha — sinha, 
e" = coshJ + sinhi, e~ 6 = cosh& — sinhi. 

The analogy between these formulae and the corresponding 
trigonometrical formulae is clear. The only difference in the 
addition theorems is one sign in the first formula. 

A corresponding analogy holds for the differentiation for- 
mulae. Eemembering that d(e x )ldx = e*, we readily find that * 

— cosh a; = sinha;, — sinha; = cosha;, 
ax dx 

d * v. 1 d ^ 1 

— tannaj = — — -, — - cotha; = — . 

ax cosh 2 a; dx smh 2 aj 

3. The Inverse Hyperbolic Functions. 

To the hyperbolic functions a;=cosh«, y=sinh«, there 
correspond inverse functions, which we denote f by 

t = ar coshx, t = ar sinhy. 

Since the function sinhi is monotonic increasing throughout the 
interval — oo < t < -f- oo , its inverse function is uniquely de- 
termined for all values of y; on the other hand, we learn from a 
glance at the graph (cf. fig. 17, p. 184) that t = ar cosha; is not 
uniquely determined, but has an ambiguity of sign, for to a 
given value of x corresponds not only the number t but also 
the number —t. Since coshZ ^ 1 for all values of t, its inverse 
ar cosha; is defined only for x ^ 1. 

We can express these inverse functions very easily in terms 
of the logarithm, by regarding the quantity e* = u in the de- 
finitions 

e* + e~* e* — er* 

2 " 2 

as unknown and solving these (quadratic) equations for u. Then 

«-=*±V(a^-l), «=y+V(y 2 +l); 

since w = e* can have only positive values the square root in 

*It is sometimes convenient to introduce the functions secha; = 1/cosha:, 
cosechz = 1/sinha;. 

t The notation cosh- 1 *, &c, is also used; cf. footnote, p. 148. 



Ill] THE HYPERBOLIC FUNCTIONS 187 

the second equation must be taken with the positive sign, while 
in the first either sign is possible. In the logarithmic form, 

t = log(a; +-\/(a? — 1)) = ar coshaj, 
t = \ g(y -f -v/(y 2 + 1)) = ar sinhy. 

In the case of ar cosh a; the variable x is restricted to the interval 
x ^ 1, while ar sinhy is defined for all values of y. 

The formula gives us two values, log {a; + */(x* — 1)} and 
log {a; — VO" 2 — !)}> f° r arcosha;, corresponding to the two 
branches of ar cosh a;. Since 

{x + V(^ - 1)} {x - V(^ - 1)} = 1 

the sum of these two values of ar cosh a; is zero, which agrees 
with a remark made above. 

The inverses of the hyperbolic tangent and hyperbolic co- 
tangent can be defined analogously, and can also be expressed 
in terms of logarithms. These functions we denote by ar tanha; 
and ar cotha;; and, expressing the independent variable every- 
where by x, we readily obtain 

1 1 + x 

ar tanha; = - log - in the interval — 1 < x < 1, 

2 1 — a; 

1 x4- 1 . 

ar cotha; = - log in the intervals x < — 1, x > 1. 

2 x — 1 

The differentiation of these inverse functions may be carried 
out by the reader himself; here he may make use of either the 
rule for differentiating an inverse function or the chain rule in 
conjunction with the above expressions for the inverse functions 
in terms of logarithms. If a; is the independent variable, the 
results are 

d , , 1 d . . i 

— ar cosha; = + — — , — arsinha;: 



dx - v^z 2 — 1)' dx Vfx 2 + 1)' 

— - ar tanha; = -, — ar cotha; = 



dx 1 — x 2 ' dx 1 — x 2 

The last two formulae do not contradict each other, since the 
first holds only for — 1 < x < 1 and the second only for x < — 1 

and 1 < x. The two values of -j- ar coshx, expressed by the 

dx 



188 DIFFERENTIATION AND INTEGRATION TChap. 



sig 11 i i* 1 * ne first formula, correspond to the two different 
branches of the curve y = ar cosh a; = log {a; +-\/(x 2 — 1)}. 

4. Further Analogies. 

In the above representation of the rectangular hyperbola by the quan- 
tity t we did not attempt to bring out any geometrical meaning of the 
"parameter" t itself. We shall now return to this matter, thus gaining still 
more insight into the analogy between the trigonometric functions and the 
hyperbolic functions. If we represent the circle with equation a? -\- y a = 1 
by means of a parameter t in the form x = cost, y = sint, we can interpret 
the quantity t as an angle or as a length of arc measured along the cir- 
cumference; we may, however, also regard t as twice the area of the cir- 
cular sector corresponding to that angle, the area being reckoned positive 
or negative according as the angle is positive or negative. 




y\ 


, 








*?-f->/ 






■t-cotkt-^4 


4j 












MM 


'1 







4-COSflt \ H 




*x 



Fig. ao. — Parametric representation 
of the hyperbola 



Fig. 21. — To illustrate the hyperbolic 
functions 



We now make the analogous statement that for the hyperbolic func- 
tions the quantity t is twice the area oi the hyperbolic sector* shown 
shaded in fig. 20. The proof is obtained without difficulty if we refer the 
hyperbola to its asymptotes as axes by means of the transformation 
of co-ordinates 

x—y=V2l, a;+y=V'2Yi, 
or 



with these new co-ordinates the equation of the hyperbola is %t\ = £. 
We thus see immediately that the area in question is equal to the area 
of the figure ABQP; for the two right-angled triangles OPQ and OAB 

* Just as the notation I = arc cos a; recalls that t is an are of a circle of 
reference, so t = arcoshz recalls that ( is a certain area connected with a 
rectangular hyperbola. 



III1 THE HYPERBOLIC FUNCTIONS 189 

have the same area, according to the equation of the hyperbola. The 
two points A and P obviously have the co-ordinates 

V2 V2 V2 ' V2 

respectively, and for double the area of our figure we thus obtain 
f U+y)lV2 
2 / (l/2r)) dyj = log(a: + y) = log { x ± V(x» - 1)}. 

•'l/v'2 

Comparison of this expression with the formula of p. 187 for the inverse 
function <= arcosha; shows us that our statement about the quantity t 
is true. 

In conclusion, it may be pointed out that, as shown in fig. 21, the 
hyperbolic functions can be diagrammatically represented on the hyper- 
bola, just as the trigonometric functions can be represented on the circle.* 

Examples 

1. Prove the formula 

sinha + sinhft = 2 sinh( a+6 ) cosh( a ~ 6 ). 

Obtain similar formulae for sinha — sinhft, cosha + cosh 6, cosh a — cosh 6. 

2. Express tanh(a ± 6) in terms of tanha and tanhfi. 
Express coth(a ± 6) in terms of cotha and cotkfc. 
Express sinhfa and cosh Ja in terms of cosha. 

3. Differentiate 

(a) cosha; + sinha:; (6) e tanh*+coth*. ^ logg^},^ + cosh'x); 
{d) ar cosha: -f ar sinha;; (e) arsinh(acoshx); (/)artanh : 



1-fa: 2 



4. Calculate the area bounded by the catenary y = cosha;, the ordinates 
x — a and x = b, and the z-axis. 

9. The Obdee of Magnitude of Functions 

The various functions that we have met in this chapter 
exhibit very important differences as regards their behaviour 
for large values of the argument or, as we also say, in the order 

* The numerical values of the hyperbolic functions, which are useful in a 
variety of calculations, are to be found in many tables. We may mention the 
following: J. B. Dale, Five-figure Tables of Mathematical Functions (Arnold, 
1918); K. Hayashi, FUnfstellige Tafeln der Kreis- und Byperbelfunktionen 
(Berlin, 1930); E. Jahnke and F. Emde, FunUionentafeln mit Formeln und 
Kurven (German and English, Leipzig, 1933). 



190 DIFFERENTIATION AND INTEGRATION [Chap. 

of magnitude of their increase. On account of the great importance 
of this we shall here discuss the matter briefly, even although it 
is not directly connected with the idea of the integral or of the 
derivative. 



1. The Concept of Order of Magnitude. The Simplest Cases. 

If the variable x increases beyond all bounds, then when 
a > the functions x*, log a;, e x , e°* will also increase beyond 
all bounds. As regards the manner of this increase, however, 
we can immediately point out an essential difference between 
them. For example, the function x 3 will become infinite to a 
higher order than a; 2 ; we mean thereby that as x increases the 
quotient aP/x* itself increases beyond all bounds. Similarly, we 
shall say that the function af becomes infinite to a higher order 
than a^ if a > /? > 0, and so on. 

Quite generally, we shall say of two functions /(a;) and g(x) 
whose absolute values increfie with x beyond all bounds that 
f(x) becomes infinite of a higher order than g(x), if as x increases 



the quotient 



9(x) 



increases beyond all bounds; we shall say 



that f(x) becomes infinite of a lower order than g{x) if the 



quotient 



9( x ) 



tends to zero as x increases; and we shall 



say that the two functions become infinite of the same order of 



magnitude if as a; increases the quotient 



/(*) 



9( x ) 



possesses a limit 



different from or at least remains between two fixed positive 
bounds. For example, the function ax 3 -\- bx 2 + c =f(x), where 
a 4= 0, will be of the same order of magnitude as the function 



9( x ) 



as? -\-bx 2 + c 
~aT 



has the 



the function x 3 + x -\- 1 becomes 



x z = g(x); for the quotient 

limit \a\. On the other hanc 

infinite of a higher order of magnitude than the function 

x*+z+l. 

A sum of two functions f(x) and <f> (x), where f(x) is of higher 
order of magnitude than <f> (x), has the same order of magnitude 



as f{x). For 



f(x)+<f,(x) 



/(*) 






and by hypothesis 



this expression tends to 1 as a: increases. 



Ill] ORDER OF MAGNITUDE 191 

We might be tempted to measure the order of magnitude of 
functions by a scale, assigning to the quantity x the order of 
magnitude 1 and to the power x* (a > 0) the order of magnitude 
a. A polynomial of the n-th degree then obviously has the 
order of magnitude n; a rational function, the degree of whose 
numerator is higher by h than that of the denominator, has 
the order of magnitude h. 

2. The Order of Magnitude of the Exponential Function and of 
the Logarithm. 

It turns out, however, that any attempt to fix the order of 
magnitude of arbitrary functions by the above scale must end in 
failure. For there are functions that become infinite of higher order 
than the power of of x, no matter how large o is chosen; again, 
there are functions which become infinite of lower order than the 
power x*, no matter how small the positive number a is chosen. 
These functions therefore will not fit in anywhere in our scale. 

Without entering into a detailed theory of the order of magni- 
tude we shall prove the following theorem: 

If & is an, arbitrary number greater than 1, then the quotient 

a x 

— tends to infinity as x increases. 

To prove this we construct the function 

qX 

(f>{x) — log — = x logo — logo; 
x 

it is obviously sufficient to show that this increases beyond all 

bounds if as tends to -f°°- For this purpose we consider the 

derivative 

<f>'(x) = loga — - 
x 

2 

and notice that for x ^ = - — - this is not less than the 

1 g0 

positive number - loga. Hence it follows that f or x ^ 

<l>(x) — <f>(c) =f<f>'(t)dt ^J\ logo dt ^ £(3 — c) loga, 

Hz) ^<f>(c) + %(x — c) loga, 
and the right-hand side becomes infinite as x increases. 



192 DIFFERENTIATION AND INTEGRATION [Chap. 

We shall give a second proof of this important theorem. 
If we write \/a = b = 1 + h, we have b > 1 and h > 0. 
Let n be the integer such that n ^ a; < n + 1; we may take 
a; > 1, so that n ^ 1. Applying the lemma of p. 31, we have 



l/a x \_ 6* 



(1+A)* (1 + A)» 1 + wA ^ wA h , 



so that 



V* V^+i) V( n + l ) V2n V 2 



a" A 2 
x > 2- W ' 



and therefore tends to infinity with x. 

From the fact just proved many others follow. For 
example, for every positive index a and every number o > 1 
the quotient a'/x* tends to infinity as x increases; that is: 

The exponential function becomes infinite of a higher order of 
magnitude than any power of x. 

In order to see this, we need only show that the a-th root of 
the expression, that is, 

a*'° _ 1 a"i a _ 1 a* / _ A 
x a x/a ay \ a/' 

tends to infinity. This, however, follows immediately from the 
preceding theorem, when x is replaced by y = x/a. 

We can prove the following theorem in a similar fashion. 
For every positive value of a the quotient (logajj/x" tends to 
zero when x tends to infinity; that is: 

The logarithm becomes infinite of a lower order of magnitude 
than any arbitrarily small positive power of x. 

The proof follows immediately if we put log a; = y, by which 
our quotient is transformed into y/e ay . We then put e* = a; 
then a is a number > 1, and our quotient y/a y approaches 
as y increases. Since y approaches infinity as x does our theorem 
is proved.* 

* Another very simple proof may be suggested: for x > 1 and e > 

log* -J"^ <f*e- 1 d£ -£(*•- 1); 

if we choose e smaller than a and divide both members of this inequality by x", 
then as x — *■ oo it follows that (logx)jx°- -> 0. 



Ill] ORDER OF MAGNITUDE 193 

With these results as a basis we can construct functions of 
an order of magnitude far higher than that of the exponential 
function and other functions of an order of magnitude far lower 
than that of the logarithm. For example, the function e** is of 
a higher order than the exponential function, and the function 
log log a; of a lower order than the logarithm; and we can obvi- 
ously repeat these iteration processes as often as we like, piling 
up the symbols e or log to any extent we please. 

3. General Remarks. 

These considerations show that it is not possible by systematic 
reasoning to assign to all functions definite numbers as orders 
of magnitude in such a way that when two functions are com- 
pared the function of the higher order of magnitude has the 
higher number. If, for example, the function a; is of the order 
of magnitude 1 and the function a^+* of the order of magnitude 
1 + e, then the function x logic must be of an order of magnitude 
that is greater than 1 and less than 1 + e no matter how small 
e is chosen. But there is no such number. Apart from this, 
however, it is easy to see that functions need not possess a clearly 
denned order of magnitude. For example, the function 
a^sina;) 2 -f x + I ,„.,.. 

~- — approaches no definite limits as x increase; on 

ar(cosa;) <! -\- x ' 

the contrary, for x = rnr (where n is an integer) the value is 
— , while for x — ( n + - W it is (n + - W + 1 + 1 _. 

n " \ V \ V T ^ („+£),/ 

Although the numerator and denominator both become infinite, 
the quotient neither remains between positive bounds, nor tends 
to zero, nor tends to infinity. The numerator, therefore, is neither 
of the same order as the denominator, nor of lower order, nor of 
higher order. This apparently startling situation merely means 
that our definitions are not designed in such a way that we 
can compare any pair of functions. This is not a defect; we 
have no desire to compare the orders of such functions as 
the numerator and denominator above, since knowledge of the 
value of one of them gives us no useful information about 
the other. 



194 DIFFERENTIATION AND INTEGRATION [Chap. 

4. The Order of Magnitude of a Function in the Neighbourhood 

of an Arbitrary Point. 

Just as we can inquire into the behaviour of a function when 
x increases without limit, we may also ask ourselves whether 
and how functions that become infinite at the point x = £ may 
be distinguished as regards their behaviour at that point. We 

further state that the function f(x) = , becomes infinite 

\ x ~€\ 
of the first order at the point x = f , and correspondingly that the 

function ; -;- becomes infinite of the order a, provided that 

\x—g\« 

a is positive. 

We then recognize that the function e 1 "* -11 becomes infinite 

of higher order, and the function log | x — f | infinite of lower 

order, than all these powers; i.e. that the limiting relations 

Iim(|as— £|«.e*fl"-*l)=oo and lim(|as— £|» . log| x— f |) = 

hold. 

In order to see this we merely put j j = y; our state- 

ments then reduce to the known theorem on p. 192, since 
|x- f |".^l-« = eft and \x- £|-Mog| x- || = -(logy)/^ 

and y increases beyond all bounds as x tends to £ . The method 
of reducing the behaviour at a finite point to the behaviour at 

infinit y by the substitution j = y frequently proves useful. 

I*— fl 

5. The Order of Magnitude of a Function tending to Zero. 

Just as we seek to describe the approach of a function to 
infinity more definitely by means of the concept of order of 
magnitude, we may also specify the way in which a function 
approaches zero. We say that as sc-»-oo the quantity 1/x 
vanishes to the first order, the quantity x~", where a is positive, 
to the order a. We find once again that the function 1/logx 
vanishes to a lower order than an arbitrary power x~ a , that is, for 
every positive a the relation 

lim(a; -cl . log a;) = 
holds. «- >0 



HI] ORDER OF MAGNITUDE 195 

In the same way we say that for x — $ the quantity x — f 
vanishes to the first order, the quantity | x — £ | a to the order a. 
With the above results it is easy to prove the relations 

lim( I x |« . log I x I ) = 0, Iim( I x I- . *-vm» = 
*->o x ^. ' 

which are usually expressed as follows: 

The function ■ — vanishes as x -► to a lower order than 

log I x I 

any power ofx; the exponential function e" 1/w vanishes to a higher 
order than any power of x. 

Examples 

1. Compare the following functions with powers of x as regards their 
Older of magnitude as x -> 00: 

(a) e^- 1. . I* cos's 

(6) (log*)". 1/B + 

(c) sinx. to) j _- r . 1/ «- 

(i) sinha;. ^ x* — 1. 

(e) x 1 /2 sin x . arc tan *. (j ) log (a; log x). 

2. Compare the functions of Ex. 1 with e aX , e 1 "", (log a;)". 

3. Compare the functions of Ex. 1 with powers of x as x -»■ 0. 

4. Does the limit lim e*"e( — **> exist? 

5. What are the limits, as a: -> 00, of e( _ «*> and «(*"*>? 

6. Let /(a;) be a continuous function vanishing, together with its first 
derivative, for x = 0. Show that f(x) vanishes to a higher order than x 
aa * -*■ 0. 

7. show that /(„ = ff+;;tl+;;; -^ *« - ^^ 

of the same order of magnitude as a:" -m , when x -*■ 00. 

8.* Prove that e* is not a rational function. 

9.* Prove that e* cannot satisfy an algebraic equation with poly- 
nomials in x as coefficients. 



196 DIFFERENTIATION AND INTEGRATION [Chap. 



Appendix to Chapter III 

1. Some Special Functions 

From time to time we have made it clear by examples that the 
general concept of function contains many possibilities foreign 
to naive intuition. As a rule these examples were not given in 
terms of single analytical expressions. Here, therefore, we wish 
to show that it is possible to represent various typical discon- 
tinuities and abnormal phenomena by means of very simple 
expressions built up from the elementary functions. We begin, 
however, with an example in which no discontinuity is present. 

1. The Function y = e~ Vx '. 

This function (cf. fig. 22), which is defined in the first instance only for 
values of x other than zero, obviously has the limit zero as x -> 0. For by 
the transformation 1/ir* = \ our function becomes y = erf and lim e~f = 0. 

Hence in order to extend our function so that it is continuous for x = 




we define the value of the function at the point x = by the equation 
1,(0) = 0. 

By the chain rule the derivative of our function for x 4= is 1/ = — er 1 /"'. 

3? 

If x tends to 0, this derivative will also have the limit 0, as we find imme- 
diately from p. 194 et seq. At the point x = itself the derivative 

*— >o h *— >o h 

is also zero. 

If we form the higher derivatives for x #= 0, we shall obviously always 
obtain the product of the function e -1 !"' and a polynomial in 1/x, and the 
passage to the limit * -*• will always yield the limit 0. All the higher 
derivatives will likewise vanish, like y", at the point x = 0. 



Ill] 



SOME SPECIAL FUNCTIONS 



197 



Thus we see that our function is continuous everywhere and differen- 
tiable as many times as we please, and yet at the point x = it vanishes 
with all its derivatives. We shall later realize (Chap. VI, Appendix, p. 336) 
how remarkable this behaviour really is. 

2. The Function y = e~ l,x . 

We may readily convince ourselves that for positive values of x this 
function behaves in the same way as the function just dealt with; if x 
tends to through positive values the function tends to 0, and the same 
is true of all its derivatives. If we define the value of the function at 




x = as y(0) = 0, all the right-hand derivatives at the point x = will 
have the value 0. It is quite another matter when x tends to through 
negative values; for then the function and all its derivatives become 
infinite, and left-hand derivatives at the point x = do not exist. At the 
point x = 0, therefore, the function has a remarkable sort of discontinuity, 
quite unlike the infinite discontinuities of rational functions considered 
on pp. 22, 53 (of. fig. 23). 



3. The Function V = tanh — . 

X 

We have already seen on pp. 33, 52 that functions with " jump " dis- 
continuities can be obtained from simple functions by a passage to the 
limit. The exponential function denned on p. 171 and the principle of 
compounding of functions give us another method for constructing functions 
with such discontinuities from elementary functions, without any further 
limiting process. An example of this is the function 

. , 1 e 1 '* — e- 1 /* 
y = tanh 



«!/• 



+ e' 



-1/a 



and its behaviour at the point x = 0. The function is in the first instance 



198 DIFFERENTIATION AND INTEGRATION [Chap. 

not defined at this point. If we approach the point x = through posi- 
tive values of x, we obviously obtain the limit 1; if , on the other hand, we 
approach the point x = through negative values, we obtain the limit — 1. 

The point x = is therefore a 
point of discontinuity; as x 
increases through the value 
of the function jumps by 2 (cf. 
fig. 24). On the other hand, the 
^_ derivative 



y, 


, 






/ 




^^tanhji 







-/ 




—•a 



y' = - 



cosh 2 (l/a;) x* 



Fig. 24 



a? ( e i/« _|_ e -i/»)a 



approaches the limit from both sides, as follows readily from * § 9, 
p. 194. 



4. The Function y = x tanb. — . 

x 



In the case of the function 

1 e l/* _ e -i/« 
y = xtann- = x —, TT - 

* x e i/« _|_ e -l/» 

the above discontinuity is removed by the factor x. This function has 
the limit as x -*■ from either side, so that we can again appropriately 




Fig. 25 



define y(0) as equal to 0. Our function is then continuous at x = 0, but 
its first derivative 

y = tanh - — 



x x cosh* (1 /a;) 



* Another example of the occurrence of a " jump " discontinuity is given 
by the function y — arc tan - as x -* 0. 



Ill] SOME SPECIAL FUNCTIONS 199 

has just the same kind of discontinuity as the preceding example. The 
graph of the function is a curve with a corner (cf. fig. 25); at the point 
x = the function has no actual derivative, but a right-hand derivative 
with the value +1 and a left-hand derivative with the value —1. 

5. The Function v = x sin -, ,y(0) = 0. 

x 

We have already seen that this function is not composed of a finite 
number of monotonia pieces — as we may say, it is not " sectionally * 
monotonio " — but that it is nevertheless continuous (p. 54). Its first 
derivative 

y" = sin cos -, tx 4= 0) 

XXX 

on the contrary, has a discontinuity at x = 0; for as x tends to this deri- 
vative oscillates oontinually between bounding curves, one positive and one 
negative, which themselves tend to + 00 and — 00 respectively. At the 

actual point * = the difference quotient is "^ ' ~ M ' — gju _. Bmce 

h h 

as A-»-0 this swings backwards and forwards between 1 and —1 an 
infinite number of times, the function possesses neither a right-hand 
derivative nor a left-hand derivative. 

2. Remarks on the Differentiability op 
Functions 

The derivative of a function which is continuous and has a 
derivative at every point need not be continuous. 

As the simplest example of this we consider the function 

1 



y — f( x ) = a 2 sin 



x 



This function is in the first instance not defined at x = 0; we shall define 
/(0), its value there, as 0, so that the function is now defined and con- 
tinuous everywhere. For all values of x different from zero the derivative 
is given by the expression 

/'(*) = —x* cos + 2x sin - = —cos - + 2x sin-. 

x 3? x x x 

When * tends to 0, f'(x) has no limit. If, on the other hand, we form the 

difference quotient J( ' ^ = ( h* sin - ) /A = h sin -, we see at once that 
ft \ ft' ft 

this tends to as a does. The derivative therefore exists for x = 0, and 
* Ger. stllckweise; of. p. 438, footnote. 



200 DIFFERENTIATION AND INTEGRATION [Chap. 

has the value 0. In order to grasp intuitively the reason for this para- 
doxical behaviour we represent the function graphically (cf. fig. 26). It 
swings backwards and forwards between the curves y = a 2 and y = — x 2 , 
which it touches alternately. Thus the ratio of the heights of the wave- 
crests of our curve and their distances from the origin steadily becomes 
smaller. Yet these waves do not become flatter; for their slope is given 

2x sin cos -; at the points x = where 

X X 2«7t 

cos - = 1 this is equal to — 1, and at the points x = — where 

x (2» + 1)71 

cos = — 1 it is equal to + 1. 

x 



3. ,.'''/\ 



by the derivative /'(*) = 




Fif?. 26 



In contrast to the possibility illustrated here, that a deri- 
vative may exist everywhere and yet not be continuous, we 
state the following simple theorem, which throws light on a 
whole series of earlier examples and discussions: if we know 
that in a neighbourhood of a point x = a the function f(x) is 
continuous and has a derivative f'{x) everywhere, except that 
we do not know whether /'(a) exists, and if in addition the equa- 
tion lim f'(x) — b holds, then the derivative f\x) exists at the 

point a also, and f'(a) = b. The proof follows immediately from 

the mean value theorem. For we have — '- — i±-' =/'(!), 

n 

where $ is a value intermediate between a and a + h. If A now 

tends to 0, by hypothesis /'(£) tends to 6, and our statement 

follows at once. 

A companion theorem to this is the following, which may 

be proved in a similar way: if the function f(x) is continuous 



Ill] DIFFERENTIABILITY OF FUNCTIONS 201 

in a^x^b and for a < x < b possesses a derivative which 
increases beyond all bounds as x tends to a, then the right-hand 

difference quotient -^i- X— £ — =^i-J also increases beyond all 

h 

bounds as h tends to 0, so that no finite right-hand derivative 

exists at x = a. The geometrical meaning of this state of affairs 

is that at the point with the (finite) co-ordinates (a, /(a)) the 

curve has a vertical tangent. 

3. Some Special Formula 

1. Proof of the Binomial Theorem. 

Our rules for differentiation enable us to give a simple proof 
of the binomial theorem; this proof will be introduced here as 
an example of the method of undetermined coefficients which we 
shall find important later. We wish to expand the quantity 
(1 + x) n in powers of x for all positive integral values of n. We 
see at once that the function (1 + »)" must be a polynomial of 
degree n, i.e. it must be of the form 

(1 + x) n = a + OjX + a 2 x 2 + ... + a n x n , 

and the problem now is to determine the coefficients a„. If we 
put x = 0, we at once obtain a = 1. If we differentiate both 
sides of the equation once, twice, three times, &c, we obtain 
the equations 

n(l + x)"- 1 =<h+ % a 2 x + • • • + ncbnX"- 1 , 
n(n - 1) (1 + x) n ~ z = 2a a + 3 . 1a z x + . . . + n{n — l)a n x n ~\ 

Since these equations hold for all values of x, we can put x = 
in each of them and thus obtain for the coefficients %, a 2 , . . . the 
expressions 

_ n(n — 1) _ n(n — 1) {n — 2) 



<h 



1.2 3 1.2.3 



n(n — 1) (n — 2) . . . (n — k + 1) _ (n\ 

a * = i! W" 

We thus finally obtain the binomial theorem in the form 
(l + x)»=l + nx+(^x*+...+ (fyx>°+... + x" 



202 DIFFERENTIATION AND INTEGRATION [Chap. 

2. Successive Differentiation. Leibnitz's Role. 

In connexion with the above we leave the reader to prove 
as an exercise that the successive differentiation of a product may 
be performed according to the following rule (Leibnitz's rule): 

dn i fa) _ *'/ a ■ m dn -v fr i m dn -y d2 9 + 

dx« KJ9) ~dx» 9 ^V/ dx"- 1 dx ^ \y dx»~* dx*^'" 



(.-0 



dfd»- 1 g + ,d»g 
dx dx"- 1 dx n ' 



The repeated differentiation of a compound function y = /{<£(«)}, 
however, follows no such easily remembered law. From the rules 
for differentiation in last chapter (the product rule and the chain 
rule) we have 

dy = df_d4 = ,,^ 
dx d<f> dx 

g=/"<P +/'<£", 
g=/»'fi + 3/"W"+/'f". 



3. Farther Examples of the Use of the Chain Rule. The Dif- 
ferentiation of fix)* 1 **. The Generalized Mean Value 
Theorem. 

To form the derivative of the function x°° we write x x = e xl °z x , 
whence we obtain 

_ X" =!B"(l0gX -f 1) 

dx 

by the chain rule. Similarly, we can carry out the differentiation 
of the more general expression f(x)K x) — e'( z > l0 * /(a,) by means 
of the chain rule, in the following way: 

^{/(*)*-»} =/(*)*<> .f'(x){logf(x) + 1}. 

As a further application of the chain rule we here give a proof 
of the theorem which we have already called the generalized 



Ill] SOME SPECIAL FORMULA 203 

mean value theorem of the differential calculus (p. 135), the 
theorem being established here under less stringent conditions. 
Let G(x) — u be a function which in the closed interval a ^ x ^ b 
is continuous and monotonic, and which in the open interval 
a < x < b has a derivative which is nowhere equal to 0, and let 
F(x) be a function which is also continuous for a <S x ^ b and 
differentiable for a < x < b. By means of the inverse function 
x = $>(u) of G(x) we introduce the new independent variable 
u instead of a; in F(x), thus obtaining the compound function 
f(u) = F(<$>(u)); according to the chain rule, 

/'( M )=^'(s)<D'( M )=J|| 

The ordinary mean value theorem, applied to the function /(«) 
and to the interval between v^ = G(a) and Mg = G(b), shows 
us that for an intermediate value a> 

f(u 2 )-f(u 1 ) _ f , F(b)-F(a) _F'(£) 

M,-^ JK } G(b)-G(a) G'(£)' 

where £ = $(«) is a value intermediate between a and b. 

Examples 

1. Find the 3econd derivative of f[g{h(x)}]. 

2. Differentiate the following functions: 
(a) x*»*. (6) (cosa;)""*. 

(C) log,^, »(*)» (that is, the logarithm of u(x) to the base v(x); v(x) > 0). 

3. Prove Leibnitz's rule. 

4. Find the »-th derivative of: 

(a) x*t?*. (d) cos mx sin kx. 

(6) (loga:) 2 . (e) e*oos2a;. 

(c) sina; sin2x. (/) (1 + x)°e*. 

6.* Find the n-th derivative of arc sina: at x = 0, and then that of 
(arc sina;) 2 at x = 0. 



6. Prove that S k(k - 1) (^) = n(n - l)2"-\ 



CHAPTER IV 

Further Development of the Integral 
Calculus 

The rules for differentiation which we formulated in the pre- 
ceding chapter have given us extensive powers over the problem 
of differentiating given functions. Almost always, however, the 
inverse problem of integration greatly exceeds it in importance. 
Hence we must now study the art of integrating given functions. 

The results attained by means of our differentiation formulae 
may be summed up as follows: 

Every function which is formed from the elementary functions 
by means of a " closed expression " * can be differentiated, and its 
derivative is also a closed expression formed from the elementary 
functions. 

On the other hand, we have not met with any exactly corre- 
sponding fact applying to the integration of elementary functions. 
We do know that every elementary function, and, in fact, every 
continuous function, can be integrated, and we have integrated 
a large number of elementary functions either directly or by 
inversion of differentiation formulae and have found their in- 
tegrals to be expressions involving elementary functions only. 
But we are still far from being able to find a general solution of 
the following problem: given a function /(x) which is expressed 
in terms of the elementary functions by any closed expression, 

to find an expression for its indefinite integral, ^"(a;) = lf(x)dx, 

which is itself a closed expression in terms of the elementary 
functions. 

* By this we mean a function which can be built up from the elementary 
functions by repeated application of the rational operations and the processes 
of compounding and inversion. 

In this connexion it should, however, be emphasized that the distinction 
between " elementary " functions and others is in itself quite arbitrary. 

204 



[Chap. IV] ELEMENTARY INTEGRALS 205 

The fact is that this problem is in general insoluble; it is by 
no means true that every elementary function has an integral 
which itself is an elementary function. In spite of this, it is 
extremely important that we should be able actually to carry 
out such integrations when they are possible, and that we should 
acquire a certain amount of technical skill in the integration of 
given functions. 

The first part of this chapter will be devoted to the develop- 
ment of devices useful for this purpose. In this connexion we 
would expressly warn the beginner against merely memorizing 
the many formulae obtained by using these technical devices. 
The student should instead direct his efforts towards gaining a 
clear understanding of the methods of integration and learning 
how to apply them. Moreover, he should remember that even 
when integration by these devices is impossible the integral 
does exist (at least for all continuous functions), and can actually 
be calculated to as high a degree of accuracy as is desired by 
means of numerical methods which will be developed later 
(Chap. VII, p. 342). 

In the latter part of the chapter we shall endeavour to deepen 
and extend our conceptions of integration and integral, quite 
apart from the problem of the technique of integration. 

1. Elementary Integrals 

First of all we repeat that to each of the differentiation 
formulas proved earlier there corresponds an equivalent integra- 
tion formula. Since these elementary integrals are used time and 
again as materials for the art of integration, we collect them in 
a table (p. 206). The right-hand column contains a number of 
elementary functions, the left-hand column the corresponding 
derivatives. If we read the table from left to right we obtain 
in the right-hand column an indefinite integral of the function 
in the left-hand column. 

We would also remind the reader of the fundamental theorems 
of the differential and integral calculus, proved in Chap. II, 
§ 4 (p. 117), in particular, of the fact that the definite integral 
is obtained from the indefinite integral F(x) by the formula 



ff(x)dx=F(x) 



= F(b) - F(a). 



206 



THE INTEGRAL CALCULUS 



[Chap. 







J"(») = 


/(*) 


1. 


x° (a 


*-l). 




2. 


1 

X 






3. 


d". 






4. 


a x (a 


*!)• 




5. 


sing. 






6. 


cos a; 







F{x) = lf(x)dx 



7. — — (s cosec 2 x). 
sin 2 a; 

8. -L- (==sec 2 x). 

p,na a a: 



9. 
10. 

11. 

12. 
13. 
14. 
15. 
16. 

17. 



oos'x 
sinhx. 
coshx. 

1 
sinh 2 x 

1 
cosh 2 a; 



(s cosech'x). 
(= sech 2 x). 



— k(|-I<D. 



V(l-x 2 ) 
1 

1 + x 2 ' 

1 
V(l + x 2 )' 

1 
±V(x 2 — 1) 

| x | < 1 
1*1 >1 



( I * | > 1). 



1 



S" 



xM 
a+ 1* 

log | x \. 



a" 
logo* 
— cosx. 
sinx. 

—cot*. 

tanx. 

coshx. 
sinhx. 

— cothas. 

tanhx. 

{arc sinx. 
— arc cosx. 
aro tanx. 
arc cot a:. 



far< 



ar sinhx = log{x + V(l -f- x 2 ) }. 
ar coshx = log{x ± Vfx 2 — 1) }. 



ar tanhx = - log — —. 
2 1 — x 

, , 1 . X + 1 

ar cothx = - log — ■ 

2 x- 1 



IV] ELEMENTARY INTEGRALS 207 

Finally, for the technique of integration the reader should 
have the elementary rules of integration collected in Chap. II, 
§ 1 (pp. 81-82) at his finger-tips. 

In the following sections we shall attempt to reduce the 
calculation of integrals of given functions in some way or other 
to the elementary integrals collected in this table. Apart from 
devices which the beginner certainly could not acquire syste- 
matically, but which, on the contrary, occur only to those with 
long experience, this reduction is based essentially on two useful 
methods. Each of these methods enables us to transform a given 
integral in many ways; the object of such transformations is to 
reduce the given integral, in one step or in a sequence of steps, 
to one or more of the elementary integration formulae given 
above. 



2. The Method op Substitution 

The first of these useful methods for attacking integration 
problems is the introduction of a new variable (i.e. the method 
of substitution or transformation). The corresponding integral 
formula is just the chain rule of the differential calculus expressed 
in the integral form. 

1. The Substitution Formula. 

We suppose that a new variable u is introduced into a func- 
tion F(x) by means of the equation x = <f>(u), so that F(x) 
becomes a function of u: 

F(x) = F(</>(u)) = G(u). 
By the chain rule of the differential calculus 
dG dF 
Ji^H + M' 

If we now write 

F'(x)=f(x) and G'(u) = g(u), 
or the equivalent expressions 

F(x) = f f( x )dx and G(u) = j ' g{u)du, 



ao8 THE INTEGRAL CALCULUS [Chap. 

then on the one hand the chain rule takes the form 

and on the other hand G(u) — F(x) by definition, that is, 

J g{u)du = jf{x)dx, 

and we obtain the integral formula equivalent to the chain rule, 

//(#«)) f («) du = ff(x) dx, {x = flu)}. 

This is the basic formula for the substitution of a new variable in an 
integral. It means that if we wish to find an indefinite integral of 
a function of u, which is given in the special form /(<£(«))<£'(«), 
then we can instead find the indefinite integral of the function 
f(x) as a function of x and after integration return to the variable 
m by putting x = <f>{u). ,,,. 

If, for example, we apply the formula to the integrand £-— 
we obtain T 

f*Mdu= /"*?=]og|*Hlog|-«u)| 
J <p(u) J X 

or, replacing u by x, 

[&dx=log\<l>(x)\. 
J <}>{x) 

If in this important formula we substitute particular functions, such as 
<f(x) = log a or <f(x) = sin x or <p(x) = cos a;, then we obtain* 

f —JL-= log | log x |, 
J a; log a; 

/ cot xdx = log | sin x\, J tan xdx = —log | cos x \. 

A further example is 

/ <p(u)<?'(u)du = / xAx= 2 a;2 = gl/PMP. 

where f(x) = *. This yields for <p(u) = logw 

J u 2 

* These and the following formulae are verified by showing that differentia- 
tion of the result gives us back the integrand. The formulae, moreover, are 
of course only asserted as true in so far as the expressions occurring in them 
have a meaning. 



IV] THE METHOD OF SUBSTITUTION 209 

We finally consider the example 

/ sin n « cos udu. 

Here x = sin w = 9 («), and hence 

/r x"* 1 sin™* 1 11 

sin»« cos«d« = J x»dx = —^ = -^p-f • 

In many cases, however, we shall use the above formula in 
the reverse direction, starting with the right-hand side, the 
integral f f(x)dx. We now have to evaluate or simplify a pre- 
scribed indefinite integral F(x) = ff(x)dx by introducing the 
new variable of integration u by means of the transformation 
formula x = <f>{u), then working out the indefinite integral 

G(u)=fM(u))4>'{u)du, 

and finally replacing the variable u in this integral by x. In 
order to carry out this last step we must be certain that a definite 
value m does actually correspond to the value x, i.e. that the 
function x = </>(u) has an inverse. Accordingly we now make 
the following assumption, in which we regard x as the primary 
variable. In the interval under consideration u = tjj(x) is a mono- 
tonic differentiable function whose derivative ^'(z) does not 
vanish anywhere in the interval. The inverse function — which 
under these conditions is definite and single-valued — we denote 
by x = 4>(u); its derivative is then given by <f>'(u) = l/0'(a;). As 
the basic formula for the substitution of a new variable u in an 
integral, we obtain 

ff(x)dx= ff(+(u)) $ (u)du (u = f(x)). 

The indefinite integral J i(x)dx can be obtained by calculating 
the indefinite integral f f(^(u))^'(u)du and finally introducing x 
instead of u for the independent variable by means of the equation 

U=i/r(x). 

It is therefore not sufficient merely to express the old variable 
x in terms of the new one u, and then to integrate with respect 
to this new variable; before integrating we must multiply by 

g (E798) 



2io THE INTEGRAL CALCULUS [Chap. 

the derivative of the original variable x with respect to the new 
variable u. 

The corresponding formula for definite integration between 
two limits is 

Jj(x)dx = l (a) f(<Hu))<f>'(u)<lu. 

In the new integral we have to choose those limits of integration 
which are obtained by subjecting the old integration limits to the 
transformation x = <f> (u), u = ifi (x). 

In most applications the integrand f(x) will appear at the 
outset as a function of a function, say/(a;) = h(u), where u = ^(a;). 
It is then more convenient to write our integral formula in a 
slightly different form by identifying the expression /{^(m)} with 
the expression h{u). If for u we make the substitution u = >ji(x), 
x = 4>{u), then our transformation formula is simply 

/ h{if>(x)}dx = J h(u) — du. 

As a first example we consider the integration of the function 
f(x) = sin 2x, taking u = i/ (x) = 2x and h(u) = sin u. We have 

ax 

If we now introduce u = 2x into the integral as the new variable, then 
it is transformed, not into / sin u du, but into 

= / smudu= — - cos « = — - cos 2s; 

this may of course be verified at once by differentiating the right-hand 
side. 

If we integrate for x between the limits and rc/4, the corresponding 
limits for u are and rc/2, and we obtain 



■ . . 1 |»/ 2 1 

sm udu = cos it = -. 

2 | 2 



r/4 J /rr/2 

sin 2xdx = - I si 
2 •'o 

rdx 
—r-. Here we take 
VI 

u= ty(x)=* Vx, whence x = <p(«) = « a . Since <p'(w) = 2u, we have 
f* dx a f 2 udu „ r 2 



IV] THE METHOD OF SUBSTITUTION an 

2. Another Proof of the Substitution Formula. 

Our integration formula can also be explained in another 
and more direct manner, by aiming at the formula for definite 
integration and basing the proof on the meaning of the definite 
integral as a limit of a sum. To calculate the integral 

h(ift(x))dx 



J 



(for the case a < 6), we begin with an arbitrary subdivision of 
the interval a^x^b, and then make the subdivision finer 
and finer. We choose these subdivisions in the following way. 
If the function w = ifi(x) is assumed to be monotonic increasing, 
there is a (1, 1) correspondence between the interval a^x^Lb 
on the x-axis, and an interval a ^ u ^ /3 of the values of 
u = tli(x), where a = i/i(a), /} = i[i(b). We divide up this u- 
interval into n parts of length * Am; there is a corresponding 
subdivision of the cc-interval into sub-intervals which in general 
are not all of the same length. We denote the points of division 
of the a;-interval by x = a, x^ x 2 , . . . , x n = b and the lengths 
of the corresponding sub-intervals by 

Aast, Aa*j, .... Ax„. 

The integral we are considering is then the limit \ of the sum 

i h{f(t v )}Ax„, 

V— 1 

where the value f„ is arbitrarily selected from the v-th sub- 
interval of the a;-subdivision. This sum we now write in the 

" Ax 

form S h(u v ) — -?- Am, where m„=^(£„). By the mean value 
K-i Aw 

Ace,, 
theorem of the differential calculus -jr 1 = fii 7 )*)' where ij„ is a 

suitably chosen intermediate value of the variable u in the v-th 
sub-interval of the w-subdivision and x=<f>(u) denotes the 

* The assumption that these sub-intervals are all equal is by no means 
essential for the proof. 

t This limit exists (for Att — »■ 0) and is the integral, since on account of the 
uniform continuity of x — </>(u) the greatest of the lengths Ax tends to 
with Am. 



212 THE INTEGRAL CALCULUS [Chap. 

inverse function of u = tfi(x). If we now select the value £„ in 
such a way that f„ and tj„ coincide, i.e. £„ = ^(ij„), i\ ¥ — 0(|„). 
then our sum takes the form 

„ = i 

If we here make the passage to the limit we immediately obtain 
the expression 

f h{u) — du, 

J a dU 

as the limiting value, that is, as the value of the integral 

we are considering, in agreement with the formula given 

above. 

We have therefore proved the following theorem: 

Let h(u) be a continuous function ofnin the interval a ^ u ^ /?. 

Then if the function u = ^r(x) is continuous and monotonic and has 

a continuous non-vanishing derivative — in a ^ x ^ b, and 
^(a)=a,<A(b) = & «** 

J h{tji{x) }dx =Jh(u)dx =J h(u) — du. 

This formula exhibits the advantage of Leibnitz's notation. In 
order to carry out the substitution u = tfi(x), we need only write 

— du in place of dx, changing the limits from the original values 
du 

of a; to the corresponding values of u. 

3. Examples. Integration Formulae. 

With the help of the substitution rule we can in many cases 

evaluate a given integral / f(x)dx if we reduce it by means of a 

suitable substitution x = <f>(u) to one of the elementary in- 
tegrals in our table. Whether such substitutions exist and 
how to find them are questions to which no general answer 
can be given; this is rather a matter in which practice and 
ingenuity, in contrast to systematic method, come into their 
own. 

As an example, we shall work out the integral / 

* 8 J V{<^-^) 



IV] THE METHOD OF SUBSTITUTION 213 

by means of the substitution * x = <f>(u) = au, u = ^(x) — x/a, 
dx = adu, by which, using No. 13 of the table on p. 206, we 
obtain 

f ^_ = f adu = arc sinw= arc sin-,for | x\ < | a\. 

By the same substitution we likewise obtain 

/dx f adu 1 , 1 . x 
= / = _ arc tanw = - arc tan , 
a 2 + x 2 Ja?(l + tt?) a a a 

/dx . , x 

. = ar sinh -, 
■x/(a 2 + x 2 ) a 



f 



ar cosh -, for | x \ > | a |, 



V(a; 2 — a 2 ) a 

dx 



r dx 

J a 2 — x 2 



' - ar tanh - for | x | < | a \ 
a a 



- ar coth - for | x | > | a | 
a a 



formulae which occur very frequently and which can easily be 
verified by differentiating the right-hand side. 

In conclusion, we again emphasize the following point. In 
our substitution process we have made the assumption that the 
substitution has a unique inverse a;= </>(«), and indeed that 
iji'(x) is nowhere equal to zero in the interval under consideration. 
If our assumption is not fulfilled, application of the substitution 
formula may easily lead to wrong conclusions. If </>'(a;) = at 
isolated points of the interval of integration only, we can avoid 
these difficulties by subdividing this interval in such a way that 
ifi'(x) vanishes only at the ends of a sub-interval; we can then 
apply the substitution to each sub-interval separately .f 

* For the sake of brevity we take the liberty of writing the symbols dx 
and du separately, i.e. dx - <j/(u)du instead of dx/du = <j>'{u) (cf. pp. 106-107). 

t An application of this method at once leads to the following result, which 
applies to many special cases: if the derivative <p'(x) vanishes at a finite number 
of points, but the function ip(x) remains monotonia, then the substitution for- 
mula remains valid. 



3i4 THE INTEGRAL CALCULUS [Chap. 

3. Further Examples op the Substitution Method 

In this section we bring together a number of examples 
which the reader may consider carefully by way of practice. 

By the substitution u — 1 ± x*, du = ±2x dx, we deduce that 

In these formulae we must take either the sign + in all three places 
or the sign — in all three places. 

By the substitution u= ax+ b, du = a dx (a 4= 0), we obtain 

/ r-s = - log | ax + b |, 

J ax+ b a 

f(ax+ 6)« dx = \ (ax + 6J-+ 1 (a 4= - 1), 

J a(a + 1) 

/sin(aa; + b)dx = cos(aa; + 6); 
a 

similarly, by means of the substitution tt= cosx, du = —mixdx, we 
obtain 

/ t&nxdx= — log|oosx|, 
and by means of the substitution u = sin a;, du = cos as dx, 
I cotx dx = log | sinx | 

(of. p. 208). Using the analogous substitutions u = cosh a;, du = sinhx dx 
and u = sinhx, du = cosh a; dx, we obtain the formulae 



/ tanha: dx = log | cosha; |, 
/ cotha; dx = log | sinha: |. 



In virtue of the substitution u — - tana;, du— - sec 2 a; dx, we arrive at 

o 6 

the two formulae 

dx 1 r 1 da; 



/■ <fo = 1^ r 1 

J o» sin a a;+ 6 2 cos'* 6 2 o a . , , ' 

I — tan a a: + I 
J 6' 

= — • arc tan ( - tana; ) 



cos 2 as 



IV] THE METHOD OF SUBSTITUTION 215 

and 

artanhf - tanx) 

ab \o / 



/dx 
a 1 sin 2 * — b 1 

We evaluate the integral 



ar ooth ( - tana;). 

ab xb / 

f dx 
J sina; 



US 4R Hf X 3S 

by writing sina: = 2 sin- cos- = 2 tan- cos*-, and putting « = tan-, so 
that du=\ sec 9 - Ax; the integral then becomes 



/dx f du , 
— = / — =log 
sin a; •> u 



tan- 



2 1 
If we replaoe * by x + jt/2, this formula becomes 

r_*L-iog|t«g+j)|. 

J oosa: I \2 4/ 1 

The substitution u = 2x yields, if we also apply the known trigono- 
metrical formulae 2 cos* a; = 1 + cos 2a; and 2 sin 2 a; =1 — cos2x, the 
frequently used formulae 



and 



/ cos 2 x dx = J (x + sina; cos a;) 
/ sin* a; dx = J (x — sina: cosx). 



By the substitution x = cosm, equivalent to «= arc cos a;, 
or, more generally, x = a cosm (a =f= 0), we can reduce 

J^/il — x^dx and f\/( a2 — *?) dx 
respectively to these formulae. We thus obtain 

ly/ifl* — a?)dx = — — arc cos - + - \/(a 2 — a: 2 ). 
J 2 a 2 

Similarly, by the substitution x = a coshw we obtain the formula 

/Vfx 2 - a*)dx = - 5 ar cosh - + 5 V(^ ~ « 2 ) 
and by the substitution x= a sinhu 

/V(« 2 + a 2 )*" = ? ar sinh - + ? v> 2 + * 2 )- 



216 THE INTEGRAL CALCULUS [Chap. 

The substitution u= -, dx = -du leads to the formulae 

x M 2 

r dx 1 . a 

/ // 2 s\ = — - arc sin -, 

J xy \x i — er) a x 

r dx _ _ 1 a 

Jx^(x 2 +a 2 ) a x' 

r dx 1 , a 

/ // 2 s; = — - ar cosh -. 

J xy(cr — x 2 ) a x 

Finally, we consider the three integrals 
/ sinma; sinwa; dx, I ainmx oosnx dx, F cos mx cos nx dx, 

where m and n are positive integers. By well-known trigo- 
nometrical formulae we can divide each of these integrals into 
two parts, writing 

sinma; sinwa: = - {cos(m — n)x — cos(m + n)x}, 

sinma; cos tub = - {sin(m -f- n)x + sin(m — w)a;}, 

cosma; coswa; = - {cos(m + n)x + cos(m — n)x}. 

If we now make use of the substitutions w= (m + n)x and 
w=(m — n)x respectively, we directly obtain the following 
system of formulae: 



sinma; sinwa:<fa;= 



/si 



/ sin mx cos nx dx = 



;\ fsin(m — n)x sin(m+m)x1 ., 

j — i — — L. ij m ^ n 

2 I m—n m+n J 

1 / sin2ma:\., 

_ i x I if m = n: 

-2 \ 2m / 

r 1 fcos(m-fra)a: . cos(m— w)a;"| ., 
21 m + n m — n J 

1 /cos2ma;\ ., 



IV] THE METHOD OF SUBSTITUTION 217 

,1 f sin(m+w)x ^ sin(w— n)x \ ^ m + n ^ 
2 I m + n m— n f 

- ( + a; I 11 to = n. 

^2 \ 2m, J 



I cosmx cos nxdx= 



If in particular we now integrate from — n to -\-it, we obtain 
from these formulae the extremely important relations 

/ +w . , f0ifm4=w. 

smma;smna;aa;= < ., 
lw if to = w, 

/ sin ma; cosnxdx = 0, 

•' — IT 

r +w j 1 if to 4= n, 

/ cosma;cosna;aa;= -! ., 
J_ w [it if to = n. 

These are the " orthogonality relations " of the trigonometric 
functions, which we shall meet with again in Chap. IX (p. 438). 

Examples 

Evaluate the following integrals and verify the results by differen- 
tiation: 

1. fxe^dx. 9. f , X+1 dx. 



V(l — x*) 
dx 



I xe x *dx. 9. f 

2. [x*er*'dx. 10. f -, _. 

J J V(5 + 2x + x 1 ) 

3. fx*VT+&dx. 11. f , dx -. 

J J V(3— 2x— x*) 



5. 



' X SMdx. 12. f xdx 

X J X*— X+ ] 

dx ,„ /" a;<fcr 



f dx . 13. /" 

J »(loga;) n J 



(log a;)"' J V(x*—4x+ 1) 

6 r 3(fa 14 f ( a + V**. 
' J 9z 2 — 6a; + 2 "J V(2 + 2x— 2x*)' 

„ r dx . f dx 

" J V(z 2 - 2a;+T)' * J x* + x + 1* 



8. /"-*!-& 16. /"* 

./ 2 + 3* Ji'-i+l 

8* (B798) 



18, 
19. 
20. 
21. 



zi8 THE INTEGRAL CALCULUS [Chap. 

l-j C &x /^arotana: 

"" J * + 2a X + b- 23 - 1 T+*r dx - 

J j _ dx. 24. / cos" x sin x dx. 

I ain*xcoa'xdx. 25. f , . 

J J Vfl + Sx 2 ) 

. I BuPxcoaixdx. 26. / - dx. 

J I (1 + z 2 ) 2 

{ x*(y/l-a?Ydx. 27. /" <fc(l<a<6). 

;■■_ ds- 28. / K8in2a^(ia!. 

29. Evaluate / (1 — a;)" da: (where n is a positive integer) by sub- 
stitution, •'o 

4. Integration by Pabts 

The second useful method for dealing with integration 
problems is given by the formula for differentiating a product: 

U9Y=f'9+ff- 

1. General Remarks. 

If we write this formula as an integral formula, we obtain 
(cf. p. 141) 

f(x)g(x) =fg(x)f'(x)dx +ff(x)g'(x)dx 
<* ff(x)g' {x)dx =f(x)g(x) -fg(x)f'(x)dx. 

This formula will be referred to as the formula for integration 
by parts. The calculation of one integral is thereby reduced to 
the calculation of another integral. For if we split up the inte- 
grand of an integral jo> (x) dx into a product <a (x) = f(x) <f> (x), and 
if we can find the indefinite integral 

g{x) = J</>(x)dx 

of the one factor <f> (x), so that <f> (x) = g'(x), then by our formula 
the integral f<o(x)dx = J f{x)<f>{x)dx = J f(x)g' (x)dx is reduced 
*° J 9(. x )f'( x )dx> which in some cases can be found more readily 



IV] 



INTEGRATION BY PARTS 



219 



than the original form. Since a given function <o (x) which occurs 
as an integrand can be regarded as a product/(a;) <f> (x) = f(x)g' (x) 
in a great many different ways, this formula provides us with 
a very effective tool for the transformation of integrals. 

Written as a formula for definite integration, the formula for 
integration by parts is 

f a b f(x)9'(x)dx=f(x)g(x) [- f*g(x)f'(x)dx 

=/(%(&) -f(a)g(a) - f g(x)f (x)dx. 

For in order to obtain the formula for definite integration from 
the formula for indefinite integration (Chap. II, § 4, p. 117) 
we have only to replace the z > 
variable appearing on both 
sides in the formula for the 
indefinite integral (1) by the 
value x = b, (2) by the value 
x = a, and write down the 
difference of these two ex- 
pressions. 

A simple interpretation of 
this formula, at least with 
suitable restrictions on the 
fupctions involved, can be 
given. Let us suppose that 

y=f(x) and z — g(x) are monotonic, and that f(a) = A, 
f(b) = B, g(a) = a, g(b) = j3; we can then form the inverse 
of the first function and substitute in the equation, thus ob- 
taining 2 as a function of y. We assume that this function is 
monotonic increasing. Since dy =f'(x)dx and dz = g'(x)dx the 
formula for integration by parts can be written 




Fig. 1 



Jzdy -\-Jydz = Bfi — Aa, 



in agreement with the relation made clear by fig. 1, 

area NQLK + area PMLQ = area OMLK — area OPQN. 
The following example may serve as a first illustration: 
/ log a: dx= I logx . 1 . dx. 



220 THE INTEGRAL CALCULUS [Chap. 

We write the integrand in this way in order to indicate that we intend to 
put /(*) = log* and g'{x) = 1, so that we have /'(*) = 1/* and g(x) = x. 
Our formula then becomes 

/ log* dx = x log* — / - dx = x log* — x. 

This last expression is therefore the integral of the logarithm, as may be 
verified at once by differentiation. 

2. Examples. 

The following further examples may help the reader to grasp this 
method. 

If we put /(*) = x, g'(x) = e*, we have f'(x) = 1, g(x) = e*, and 

f x^dx = ef"(x— 1). 

In a similar way we obtain 

/ x sin* dx = —x cos* + sin* 

/ xooaxdx= xsm.x+ aoax. 
For /(*) = log*, g'{x) = x", we have the relation 

/x" log* dx = I log* — ). 

Here we must assume a 4= — 1. For a = — 1 we obtain (of. p. 208) 

/- log* dx = (log*) 3 — / log* . — ; 
* J x 

transferring the integral on the right-hand side over to the left, we have 

f\ i 

/ - log* dx = - (log*) 2 . 
J x 2 

We calculate the integral / arc sinxdx by taking /(*) = aro sin*, 
gr'(*) = 1. From this we obtain 

/arc sin* dx = * aro sin* — / — , 
J V(l - **) 

The integration on the right-hand side can be performed as in § 3 (p. 214); 
we thus find that 

/ arc sin* dx = x are sin* + V(l — X s ). 



IV] INTEGRATION BY PARTS 221 

In the same way we calculate the integral 

/ aro tana; dx = x arc tanx log (1 + x*) 

and many others of a similar type. 

The following examples are of a somewhat different nature; here a double 
application of the method of integration by parts brings us back to the 
original integral, for which we thus obtain an equation. 

Integrating by parts twice, we obtain 

/e ox sin&x dx = — - e * cos 6a; + ? / e * cosfcc dx 

<= e*" cos bx + — e?* sin bx — - I eP" sin&x dx, 

b & a 6 2 J 

and, solving this equation for the integral / e"" sin bx dx, 

/e°* ainbxdx— — ef^ia sin&x — & cos bx). 
a* + 6 a v ' 

In a similar way it follows that 

/e ax cosbx dx = e^la coabx + 6 sin&x). 
o a + 6 s ' 

3. Recurrence Formulae. 

In many cases the integrand is a function not only of the 
independent variable, but also of an integral index n, and on 
integrating by parts we obtain, instead of the value of the in- 
tegral, another similar expression in which the index n has a 
smaller value. We thus arrive after a number of steps at an 
integral which we can deal with by means of our table of integrals. 
Such a process is called a recurrence process. The following 
examples illustrate this: by repeated integration by parts we 
can calculate the trigonometrical integrals 

JcoB n xdx, jBm n xdx, j8m m xcos n xdx, 

provided that m and n are integers. For we find that 

Jcos n xdx = cos n_1 a; sina; -)- (n — l)fcoa n ~ i x sm 2 xdx; 

we can write the right-hand side in the form 

cos n_1 a; sina; + (n — 1) Jcos n ~ z xdx — (n — 1) icos n xdx, 



222 THE INTEGRAL CALCULUS [Chap. 

thus obtaining the recurrence relation 

/cos"xdx = - cos n_1 a; sina: -\ [coa n ~ 2 xdx. 
n n J 

This formula enables us to keep on diminishing the index in 
the integrand until we finally arrive at the integral 

lcoaxdx=smx or ldx = x > 

according as n is odd or even. In a similar way we obtain the 
analogous recurrence formulae 

jsia n xdx = sin n-1 a; cosa; ^ lsin. n ~ 2 xdx 

J n n J 



f ■ ™ « j sin m+1 a; cos" -1 a: . n — 1 r . _ „_, , 

/ sin" 1 ! cos n a; ax = 1- / sm m x cos" z x ax. 

J m 4- n m + n J 



In particular, these formulas enable us to calculate the integrals 

r 1 

/ sin 2 a; dx = -(x — sina; cosa;) 

/I 
cos 2 x dx = - (x + sina; cosa;), 
2 

as we have already done by the method of substitution (p. 215). 
It need hardly be mentioned that the corresponding integrals 
for the hyperbolic functions can be calculated in exactly the same 
way. 

Further recurrence formulae are given by the following transformations: 

f (log a:)™ (fas = a; (log a;)™ — ml (loga:)™- 1 ^, 

j x m e*dx = x m e?° — m j x m ^ 1 e!"dx, 

I x m wax dx = — x m cosa: + tn J x™- 1 cosa; dx, 

I x m cosx dx = x m sina: —ml a;™"" 1 sina; dx, 

f x" (loga;)™ dx = xa+1 < lo 8 g r - ™ /^"(Ioga;)™- 1 ^ (a* -1). 



IV] INTEGRATION BY PARTS 223 

4. Wallis's Product. 

The recurrence formula for the integral lsax fi xdx leads in 
an elementary way to a most remarkable expression for the 
number it as an infinite product. We suppose that ft > 1, and 
in the formula 

sin"a; dx = sin n-1 aj cosa; -\ / sin n-2 a; dx 

n n J 

we insert the limits and it/2, thus obtaining 

/•f/2 n \ /.W2 

/ wn n xdx = / ain n ~ 2 xdx for« > 1. 

•M) ft •'0 

If we again apply the recurrence formula to the right-hand side 
and continue the process, we obtain, distinguishing between the 
cases n = 2m and n = 2m + 1» 



r' 2 - ^ j 2m — 1 2m — 3 
/ aw^xdx — 
■'0 2m 2m — 2 


1 r'% 


J sin 2m+1 a!(fa; — m . m ~ . 
Jo 2m + 1 2m — 1 


2 /"•. , 

. . - . / sinasoa;, 

3 -/o 


whence 




f *'*• 2™ j 2m — 1 2m — 3 
J 2m 2m— 2 


1 it 
' 2 " 2* 


1 wi? m + 1 xdx — 
J o 2m + 1 2m — 1 


2 
'3' 


By division this yields 




■n _ 2.2 4.4 6.6 2m. 2m 
2 1.3"3.5'5.7"'(2m— l).(2m4 


y.V2 

/ sin^aidas 
•'0 

- 1} r"' 2 



The quotient of the two integrals on the right-hand side con- 
verges to 1 as m increases, as we recognize from the following 
considerations. In the interval < x < 77/2 we have 

< sin 2 ™- 1 " 1 * ^ sin 2 ™ a; ^ sin 2 ™- 1 a;: 



324 THE INTEGRAL CALCULUS [Chap. 

consequently 

J /.if/2 /.ir/2 ^ir/2 

o »o •'o 



If we here divide each term by / sin 2n,+1 a; dx and notice that by 
the first formula proved above 

/.t/2 

/ sin 2 "* -1 xdx „ . . , 

^ _ 2m + 1 _ j , 2_ 

/ sin 2 ™* 1 ^^; m m 

•'o 

/ sin 2 " 
we have 1 ^ -2-™ ^ 1 + 



-7T/2 

/ sin^xda; 

/' 



Bin im+1 xdx 



2m 



from which the above statement follows. 
The relation 

it ,.224466 2m 2m 

- = Mm 



2 m-xol 3 3 5 5 7 2m— 12m +1 

consequently holds. 

This product formula (due to Wallis), with its simple law of 
formation, gives a remarkable relation between the number it 
and the integers. If we observe that 

lim = 1, we can write 

m _>»2m+ 1 

.. 2 2 .4 2 ...(2«-2) 2 77 

lim - 2m = -, 

ffl _*oo3 2 .5 2 ...(2m-l) 2 2' 

and if we take the square root and then multiply mumerator and 
denominator by 2 . 4 . . . (2m — 2) we find that 

„ =]hn 2.4...(2m-2)^ =lim 2 2 .4 2 ...(2m-2) 2 ^ m 
2 m->oo3.5...(2m— 1) „,->«, (2m— 1)1 

= j. 2 2 .4 2 . . .(2m) 2 V2m 
m-»-ot> (2m)! 2m 



4 



IV] INTEGRATION BY PARTS 225 

From this we finally obtain 

,. (m!) 2 2 2m , 
lim / , . = Vt. 

a form of Wallis's product which will be of use to us later 
(cf. Chap. VII, Appendix, p. 363). 

Examples 
Evaluate the integrals in Ex. 1-14: 

I. [ x S2^dx. 2. f x ' dx. 3. fx^oosxdx. 
J sin 8 * J (1 — a; 4 ) 2 J 

4. / x^e-B'dx. 6. J aPcoanxdx (n a positive integer). 

6. J x^sinnxdx (n a positive integer). 7. /a? cos a? dx, 

8. f sin* x dx. 9. fcoa"xdx. 10. fx i V\ — x t dx. 

II. fx*<*dx. 12. f l ^dx (nM=l). 

13. jx m logxdx (m=#l). 14. J x* (logx)* dx. 

15. Prove the formula 

f<*p{x)dx = e*{p(z) - j>'(z) + !>"(*) - + ...}, 
where #(2:) is any polynomial. 

16. Show that for all odd positive values of » the integral / ir^x^dx can 
be evaluated in terms of elementary functions. 

17. Show that if n is even the integral / e~ x 'x n dx can be evaluated 

in terms of elementary functions and the integral / e-*"'dx (for which 
tables have been constructed). 

18. Prove that 

•'0 ^0 ' •'0 

19.* Ex. 18 gives a formula for the second iterated integral. Prove 
that the ra-th iterated integral of f(x) is given by 

_ I— f X f(u)(x-u)»-idu. 
(n— 1)\J 



226 THE INTEGRAL CALCULUS [Chap. 

5. Integration op Rational Functions 

The most important general class of functions integrable in 
terms of elementary functions consists of the rational functions 

where /(a;) and g(x) are polynomials: 

/(*) = <V" + am-ia™ -1 + . . . + a , 

g(x) = b n x" + b n _ x x»- 1 + . . . + b (b n #= 0). 

We recall that every polynomial can be integrated at once and 
that the integral is itself a polynomial. We therefore need 
only consider those rational functions for which the deno- 
minator is not a constant. Moreover, we can always assume 
that the degree of the numerator is less than the degree (ri) 
of the denominator. For otherwise we can divide the poly- 
nomial f(x) by the polynomial g(x) and obtain a remainder 
of degree less than n\ in other words, we can write 
f(x) = q(x)g(x) + r(x), where q{x) and r{x) are also poly- 
nomials and r(x) is of lower degree than n. The integration of 

f( x ) 

— — is then reduced to the integration of the polynomial q(x) 

y*" 1 ' r(x) 

and of the " proper " fraction -y-r. We further notice that the 

f(x) 9^' 

function -^-~ can be represented as the sum of the functions 

—t~z, so that we need only consider integrands of the form ~ r-r. 
g(x) J 8 g(x) 

1. The Fundamental Types. 

We shall not at once proceed to the integration of the most 
general rational function of the above type, but shall instead 
study only those functions in which the denominator g(x) is of a 
particularly simple type, namely, 

g(x) = x, g(x)=l + x i , 

or, more generally, 

g(x) = x», g(x)=(l + x*) n 

where n is any positive integer. 



IV] INTEGRATION OF RATIONAL FUNCTIONS 22J 

To this case we can reduce the somewhat more general case 
in which g(x) == (ax + j3) n , a power of a linear expression 
ax + /? (a 4= 0), or g(x) = (ax 2 -\- Ibx + c) B , a power of a 
definite * quadratic expression. In the first case we introduce 
a new variable £ = ax + £. Then d£/dx — a, and x = ($ — fl)/a 
is also a linear function of £. Each numerator /(x) becomes a 
polynomial </>(() of the same degree, and consequently 



J (ax+ B) n a J £ » 



(ax+jS) 
In the second case, we write 

ax*+2bx+c = -(ax+b) 2 + - (<P = ac - 6 2 , d > 0), 
a a 

observing that, since we have assumed our expression to be 
definite, ac— b 2 must be positive and a =4= 0. By introducing 
the new variable 

£_ ax-\-b 

? d~ 

r^2 "In 

we arrive at an integral with the denominator — (1 + {?)\ . 

Hence in order to integrate rational functions whose de- 
nominators are powers of a linear expression or of a definite 
quadratic expression it is sufficient to be able to integrate the 
following types of functions: 

1 a?" x 2 ^ 1 

X"' (x 2 + 1)"' (x* + 1)»' 

We shall, in fact, see that even these types need not be treated 
in general, for we can reduce the integration of every rational 
function to the integration of the very special forms of these 
three functions obtained by taking v = 0. Accordingly we now 
consider the integration of the three expressions 

2. 1 x 

x n ' (x 2 + 1)"' (x 2 + 1)»' 

* A quadratic expression Q(x) = ax 1 + 2bx + c is said to be definite if for 
all real values of x it takes values having one and the same sign, i.e. if the 
equation Q(x) - has no real roots. For this it is necessary and sufficient 
that ac — b 2 should be positive. 



228 THE INTEGRAL CALCULUS [Chap. 

2. Integration of the Fundamental Types. 

Integration of the first type of function, — , immediately yields the 

expression log \ x\ if n = 1, and the expression — if » > 1, 

so that in both cases the integral is again an elementary function. Func- 
tions of the third type can be integrated immediately by introducing the 
new variable $ = X s + h whence we obtain 2xdx = d% and 

Jp+ir iJv i- t (.-i)^. Mr » " n 

Finally, in order to calculate the integral 

I = f dx 
" J (s* + 1)»' 

where m has any value exceeding 1, we make use of a recurrence method. 
For if we put 

1 = 1 x* 

(a? + 1)» ~ (a? + I)"" 1 (*» + 1)"' 

da; r dx f X s dx 



"^ I vhr- ! IFTvF*- ! 



(*" + 1)» 

we can transform the right-hand side by integrating by parts, using the 
formula on p. 218 with 

Then, as we have just found above, 

1 1 



g(x) = - 



2 (ra — l){a?+ l)"- 1 

and consequently we obtain 

T _ r dx _ x 2m— 3 r dx 

* ~~ J (x> + 1)» ~ 2(n- l)(a; 2 + l)"" 1 2(n-l)J (x* + 1) 



The calculation of the integral I n is thus reduced to that of the integral 
/„_j. If n — 1 > ,1 we apply the same process to the latter integral, and 
continue the process until we finally arrive at the expression 



/ 



dx . 
= arc tanx. 

(* a + 1) 



IV] INTEGRATION OF RATIONAL FUNCTIONS 229 

We thus see that the integral * I n can be explicitly expressed in terms of 
rational functions and the function arc tana;. 

Incidentally, we could also have integrated the function 

directly using the substitution x = tant; we should then have obtained 
dx = sec 2 1 dt and 1/(1 + x 8 ) = cos* t, so that 

f — — = f cos 8 "- 2 tdt, 

J (**+ 1)» J 

and we have already learned (p. 222) how to evaluate this integral. 



3. Partial Fractions. 

We are now in a position to integrate the most general 
rational functions, in virtue of the fact that every such function 
can be represented as the sum of so-called partial fractions, 
i.e. as the sum of a polynomial and a finite number of rational 
functions, each one of which has either a power of a linear 
expression for its denominator and a constant for its numerator, 
or else a power of a definite quadratic expression for its 
denominator and a linear function for its numerator. If the 
degree of the numerator /(x) is less than that of the denominator 
g(x) the polynomial does not occur. We are now in a position 
to integrate each partial fraction. For according to p. 226 the 
denominator can be reduced to one of the special forms x n and 
(x 2 + 1)", and the fraction is then a combination of the 
fundamental types integrated on p. 228. 

We shall not give the general proof of the possibility of this 
resolution into partial fractions. On the contrary, we shall 
confine ourselves to making the statement of the theorem in- 
telligible to the reader and to showing by examples how the 
resolution into partial fractions can be carried out in typical 
cases. In actual practice only comparatively simple functions 
are dealt with, for otherwise the computations become far too 
complicated. 

* The integral of the function r -= ttt; can be calculated in the same way; 

(%* — l) n 

by the corresponding recurrence method we reduce it to the integral 



/ 



artanhx (orarcothz). 



1 - x' 



330 THE INTEGRAL CALCULUS [Chap. 

As we know from elementary algebra, every polynomial 
g(x) can be written in the form 

flr(x) = a(a;-a 1 ) l '(x-a a ) , '...(a?+26 1 a; + c 1 )"(ic 2 +26 a a; + c 2 )'''... 

Here the numbers a v a 2 , . . . are the real and distinct roots of 
the equation g(x) = 0, and the positive integers 1^1^ .. ■ indicate 
the numbers of times they are repeated; the factors x 2 + 2b v x + c„ 
indicate definite quadratic expressions, of which no two are the 
same, with conjugate complex roots, and the positive integers 
r v r 2 , . . . give the numbers of times that these roots are repeated. 
We assume that the denominator is either given to us in 
this form or else that we have brought it to this form by calcu- 
lating the real and imaginary roots. Let us further suppose that 
the numerator f(x) is of lower degree than the denominator 
(cf. p. 226). Then the theorem on resolution into partial 
fractions can be stated as follows. For each factor (x — a)', 
where a is any one of the real roots and I is the number of 
times it is repeated, we can determine an expression of the 
form 

(X- ay (x- af^ " (x- af 

and for each quadratic factor Q(x) == x 2 + 26a; + e m our 
product which is raised to the power r we can determine an 
expression of the form 

Bj, + C lX B 2 + G& B r +C,x 

Q "*" Q 2 " t ~-"~ t ~ Qr > 

fix) 
in such a way that the function ^— ' is the sum of all these ex- 

S( x ) f(x) 
pressions. In other words, the quotient -r-r can be represented 

as a sum of fractions each of which belongs to one or other of 
the types integrated on p. 228.* 

• Here we give a brief sketch of the method by which the possibility of this 
decomposition into partial fractions is proved. If g(x) — (x — a)* k(x) and 
A (a) + 0, then on the right-hand side of the equation 

M - /(") _L /(*)*(«)-/(«)*(») 

g(x) h(a)(x - a)* A(o) (Z - a)*A(z) 

the numerator obviously vanishes for x — a; it is therefore of the form 



IV] INTEGRATION OF RATIONAL FUNCTIONS 231 

In particular oases the splitting up into partial fractions can be done 
easily by inspection. If, for example, g(x) = a? — 1, we see at once that 



1 1111 

x*— 1 2 x— 1 2 x + 


1* 


f dx _ 1 i„„ | * — 1 
J a? -I 2°°|a!+l 


• 



so that 

More generally, if g(x) = (x— a)(x — P), that is, if g (x) is a non-definite 
quadratic expression with two real zeros a and (3, we have 

1 1111 



so that 



(* — a)(x — P) « — pa;— a a — p * — P 

/dx _ 1 , x — a. 

(x-a){x- p) ~ a- p ° g a- p 



4. Example. The Bimolecular Reaction. 

A simple example of the application of this easy reduction to partial 
fractions is given by the so-called bimolecular reaction. Let us suppose 
that we have two reagents whose original concentrations in mols per unit 
volume are a and b, where we assume that a < b, and let us suppose that 
in time t there is formed in the unit volume a quantity x (mols) of the 
product of reaction. Then, according to the law of mass action (cf. p. 182), 
in the simplest case — reaction between one molecule of each of the re- 
agents — the rate of increase of the quantity x is given by the equation 

dx 

rr = k(a — x)(b — x). The problem is to determine the function x(t). 

If, inversely, we think of the time t as a function of x, we have 

dt = 1 = 1 / 1 _ 1 \ 

dx k(a — a;)(6 — x) k(b — a) \a — x b — x' 

hence by integration 

kt = log + e, for x < a < b. 



h{a)(x — a) m f x (x), where f x (x) is also a polynomial, the integer m 2: 1, and 
/^a) 4= 0. Writing {^) - fl, this gives us 

IM g fi(x) 

g(x) (x - a) k (x - o)*-«»A(z)' 

Continuing the process, we can keep on diminishing the degree of the power 
of (x — a) occurring in the denominator until finally no such factor is left. 
On the remaining fraction we repeat the process for some other root of g(x), 
and do this as many times as g(x) has distinct factors. This being done not 
only for the real but also for the complex roots, we eventually arrive at the 
oomplete analysis into partial fractions. 



232 THE INTEGRAL CALCULUS [Chap. 

We determine the constant of integration c by the condition that at time 
t = no product of reaction has yet been formed, so that 

1 log? + c=0. 



a—b °b 
We thus obtain finally 

1 l ~a 

la = log , 

a—b _ x 

b 

and if we solve for x this gives the required function x(t): 

_ ab(\ — e( a - fc >**) 
6 _ aeia-ftkt 

5. Farther Examples of Resolution into Partial Fractions. The 
Method of Undetermined Coefficients. 

II g(x) = (x — ai) (a; — c^) ... (x — o„), where a t 4= o-k if 
» 4= k, i.e. if the equation g(x) = has only single real roots, the 
expression in terms of partial fractions has the simple form 

1 _ <h _|_ g 2 + # _ j_ a n 



^(a;) a; — c^ x — a% x — a„ 

We obtain explicit expressions for the coefficients %, a 2 , . . . if we 
multiply both sides of this equation by (x — o^), cancel the common 
factor (x — dj) in the numerator and denominator on the left 
and in the first term on the right, and then put x= a^. This 
gives* 

1 

Oj = . 

(«1 — a 2 ) (ci! — a 3 ) . . . (dj — a„) 

As a typical example of a denominator g(x) with multiple roots, we 

consider the function . The preliminary statement 

x*(z — 1) 

1 =_?_ + *+£ 

a?(a;— 1) x — 1 x x* 

in accordance with p. 230 leads us to the required result. If we multiply 
both sides of this equation by a; 2 (a; — 1) we obtain the equation 

1 = (a + b)x* — (6 — e)x — c, 

* The reader will observe that the denominator on the right is (^(a,), i.e. 
the derivative of the function g(x) at the point x — a,. 



IV] INTEGRATION OF RATIONAL FUNCTIONS a 33 

true for all values of x, from which we have to determine the coefficients 
a, b, c. This condition cannot hold unless all the coefficients of the poly- 
nomial (a+ ft)* 2 — (6— c)x — c— 1 are zero, i.e. we must have 
a+6=&-c=c+l = 0orc=-l, 6=-l, a=l. We thus obtain 
the resolution 

1 111 



* 2 (*-l) x-1 
and consequently 



/. 



; = log|x- 1|- log |a;|+ l 



We shall now split up the function — (which is an example of 

x(x a +1) r 

the case where the zeros of the denominator are complex) in accordance 
with the equation 

1 a bx -f c 



/, 



*(a; 2 +1) x x*+l 
For the coefficients we obtain a + b = c= a — 1 = 0, so that 

1 _ 1 x_ 

X(x 2 + 1) X X*+T 

and consequently 

*,l^T) = log l a! l-^ lo ^ 8+1 )- 

As a third example we consider the function . Even Leibnitz 

x* + 1 
found this a troublesome integration. We can represent the denominator 
as the product of two quadratic factors: 

* 4 + 1 = (a? + l) 2 - 2x* = (x* + I + V2x) (x* + 1 -V2x). 

We know, therefore, that the resolution into partial fractions will have 
the form 

1 _ ax + b ex + d 



x i +l x*+V2x+l x*— V2x+l' 
To determine the coefficients a, 6, c, d, we have the equation 

(a + c)x* + (6 + d - aV2 + cV2)x* +{a + c-bV2 + dV2)x 
+ (b + d - 1) = 0, 
which is satisfied by the values 

a=_L 6=1 C =__L d= 1 
2V2' 2' " 2V2' 2* 

We therefore have 

1 1 x+V2 1 x—V2 



x*+l 2V2*z 2 + V2x+ 1 2V2"ie»— V2x + l' 



234 THE INTEGRAL CALCULUS [Chap. 

and, applying the method given on p. 227, we obtain 

/?TT = 4V2 l0g|a!a+V ' 2a,+ 1| -4V2 l0g|a:, - V ' 2a!+11 

J L_ arc tan (V2x + 1) + _L_ arc tan (V2x — 1), 

2V2 2V2 

which may easily be verified by differentiation. 

Examples 



Integrate: 

1 f ** 8 f Ax 

' J 2x — Za?' 'Jl + J?' 

2. f_*L. 9. f , (a; - 4) dx. 
J x*-x J (x*+ l)(s-2) 

3. f 3dx . 10. f !L±i «fa. 

/• x* + x+l ^ f— A d*. 

J 3a; 2 — 2x — 6 J 1-*' 



— (2x. 
2 



f dx 12*[^L. 

J (x- lf(x* + 1) J * 6 + 1 

/a^efce ., /• a 8 

(a:— l) s (a»+l)' ' J x* + x* — 

/dx ,. r dx 

l^~x*' ' J a^+l) 2 ' 



6. Integration of Some Other Classes of Functions 

1. Preliminary Remarks on the Rational Representation of the 
Trigonometric and Hyperbolic Functions. 

The integration of some other general classes of functions can 
be reduced to the integration of rational functions. We shall 
be better able to understand this reduction if we begin by stating 
certain elementary facts about the trigonometric and hyperbolic 

functions. If we put t = tan -, elementary trigonometry gives 

2t 

us the simple formulae 

It 1 — t* 

bulx = „ , cosa; = ; 

1 + < 2 1 + t 2 



IV] 
for 



OTHER CLASSES OF FUNCTIONS 



235 



= cos 2 - and 



t* 



l + t* 2 1 + fi ' 

and hence from the elementary formulae 



= sin 2 



2' 



sinx = 2 cos 2 ~ tan ? and cosx = cos 2 - — sin 2 - 
2 2 2 2 

we obtain the above equations. These equations show that sin a; 
and cos a; can be expressed rationally in terms of the quantity 

t — tan -. From t = tan - we have by differentiation 
2i 2 

dt _ 1 __ 1 + fi dx _ 2 

dx 2cos 2 a;/2 2~* S ° ttot A ~ lTP 5 

hence the derivative — is also a rational expression in t. 
at 

The geometrical representation of our formulae and their geometrical 
meaning are given in fig. 2. Here the circle u* + v 1 = 1 in a ttt>-plane ia 
shown. If x denotes the angle POT in 
the figure, then u = cosx and v = sinx. 
The angle OSP with its vertex at the 
point u = — 1, v = is equal to x/2, by 
a theorem in elementary geometry, and 
we can read off the geometrical meaning 
of the parameter t from the figure; 
t = tan \x = OB. If the point P starts 
from S and runs once round the circle in 
the positive direction, i.e. if x runs through 
the interval from — 7c to +7r, the quantity 
t will run through the whole range of 
values from — oo to + oo exactly once. 




Fig. 2. — Parametric representation 
of the trigonometric functions 



We may correspondingly express the hyperbolic functions 
cosh a; = £(e" -f e -<°) and sinha; = £(e* — «r") as rational func- 
tions of a third quantity. The most obvious way is to put e x = t, 
so that we have 

cosha ! =l(r+^, smhx=l(r-iy 

which are rational expressions for sinha; and cosh a;. Here again 
dxjdt = 1/t is rational in t. But we obtain a closer analogy 



236 THE INTEGRAL CALCULUS [Chap. 

with the trigonometric functions by introducing the quantity 

t = tanh-t we then arrive at the formulae 
2 



Binha; = 



2f 



cosh as = 



1 + 
1- 



By differentiating t = tanh- we obtain, as on p. 235, the rational 
expression 

dx_ 2 

dt l — t 2 

for the derivative dx/dt. Here again the quantity t has a geometri- 
cal meaning similar to that which it has in the case of the trigo- 
nometric functions, as we see at once from fig. 3. 



V, 


HtM 






1* 


R 








1 




+ox" 


—coskx- 




X 













rb 


it 



pig. 3. — Parametric representation of the hyperbolic functions 

But whereas in the case of the trigonometric functions t 
must run through the whole range of values from — °o to + oo 
in order to give all pairs of values of cos a; and sin a;, in the 
case of the hyperbolic functions t is limited to the interval 

— Kt<l. 

Having made these preliminary remarks, we proceed to our 
integration problem. 

2. Integration of R(coax, sinar). 

Let 22 (cos as, sin a;) denote an expression which is rational in 
the two functions sin a; and cos a;, i.e. an expression which is 



IV] OTHER CLASSES OF FUNCTIONS 237 

formed rationally from these two functions and constants, such as 
3 sin 2 a; + cosa; 
3 cos 2 a; + sin a;' 

If we apply the substitution t = tan - the integral 

I R{cosx, sina:)efa: 
is transformed into the integral 

and under the integral sign we now have a rational function of t. 
Thus we have in theory obtained the integral of our expression, 
since we can now perform the integration by the methods of the 
preceding section. 

3. Integration of i? (cosh a;, smhx). 

In the same way, if .R (cosh a;, sinha;) is an expression which 
is rational in terms of the hyperbolic functions cosh a; and sinha:, 
we can effect its integration by means of the substitution 

t = tanh -. Recalling that 

dx 2 



dt l-* 2 
we have 



fR(coahx, sinhx)dx= fRJ^tL, yzTJ%) f^r 



-dt. 
t 2 



(According to a previous remark we could also have introduced 
t = e x as a new variable and expressed cosh a; and sinha; in terms 
of t.) The integration is once again reduced to that of a rational 
function. 

4. Integration of R{x, -\/(l — x 2 )}. 

The integral J R{x, -\/(l — x 2 )}dx can be reduced to the type 
treated in No. 2 by using the substitution 

x = cosm, \/(l — a^) = sinu, dx = — sinw du; 



238 THE INTEGRAL CALCULUS [Chap. 

froin this stage the transformation t = tan - brings us to the 

2i 

integration of a rational function. Incidentally, we could have 

carried out the reduction in one step instead of two by using 

the substitution 

dx — it 

dt~ (1 + fi/' 

that is, we could have introduced t = tan - directly as the new 
variable and thereby obtained a rational function to integrate. 

5. Integration of R{x, \/(x 2 — 1)}. 

The integral jR {x, \/(x 2 — l)}dx is transformed by the sub- 
stitution x = coshw into the type treated in No. 3 (p. 237). Here 
again we can arrive at our goal directly by introducing 

t = aII . t ) = tanh -. 



! "VV+i)' 



6. Integration of R{x, V(**+ *)}• 

The integral jR{x, -\/(x 2 + l)}dx is reduced by the trans- 
formation a;=sinhM to the type considered in No. 3 (p. 237), 
and can therefore be integrated in terms of elementary functions. 
Instead of the further reduction to the integral of a rational 

u 
function by the substitution e u = r or tanh - = t, we could have 

2* 

reached the integral of a rational function at a single stroke by 

either of the substitutions 

T-.+ V<*+l>. f-- 1 + ^*+ 1 >. 

X 

7. Integration of R{x, i/(ax* -f Zbx + c)}. 

The integral jR {x, y/(ax*-\- 2bx-\- c)}dx of an expression 
which is rational in terms of x and the square root of an arbitrary 



IV] OTHER CLASSES OF FUNCTIONS 339 

polynomial of the second degree in x can immediately be re- 
duced to one of the types just treated. We write (cf. p. 227) 

1 , , ,>, , ac — 6 2 



ax 2 + 2bx + c = ~ (ax + bf + 



a, a 



If ac — b 2 > we introduce a new variable f by means 

of the transformation f = f*"*" whereupon the surd takes 

■\/(ac — 6 2 ) 

the form J j (£2+ 1) I. Hence our integral when expressed 

in terms of $ is of the type of No. 6. The constant a must here 
be positive in order that the square root may have real values. 
If ac — b 2 = 0, a > 0, then by way of the formula 

A/(az 2 + 2bx + c) = ■y/a (x + -\ 

we see that the integrand was rational in x to begin with. 

If, finally, ac - b* < 0, we put £ = ™ +b and obtain for 

V (0 — "jC) 

the surd the expression A\ ~ ac (p _ 1)1 If a j 8 positive, 

our integral is thus reduced to the type of No. 5 (p. 238); if, on 
the other hand, a is negative, we write the surd in the form 

yj( —3 — ) V0- — €*) and see that the integral is thus reduced 

to the type of No. 4 (p. 237). 

8. Further Examples of Reduction to Integrals of Rational 
Functions. 

Of other types of functions which can be integrated by re- 
duction to rational functions we shall briefly mention two: 
(1) rational expressions involving two different surds of linear 
expressions, R{x, ^/(ax+b), ■y/{ax+ 0)}; (2) expressions of 

the form R\x, W/ ^ U, where a, b, a, fi are constants. 

In the first case we introduce the new variable $ = -\/(ax + /}), 
so that ax + /? = £* and consequently 

x^^zl and i* = 2J. 
a dg a 



24 o THE INTEGRAL CALCULUS [Chap. 

then JR{x, V(oa; + b), ^(ax + j8)} dx 

= fB {£=£. </!{«*• -<«/»-*-)}, *} ^ % 

which is of the type discussed in No. 7. 

If in the second case we introduce the new variable 

"j/ax+b\ 

we have 

ox + 6 -fig" + & & = <*£ — fa B «■-» 

f "ai+T a*"-a' d* (a£»-af 

and we immediately arrive at the formula 

/«(*V(=T?))* 

which is the integral of a rational function. 

9. Remarks on the Examples. 

The preceding discussions are chiefly of theoretical interest. 
In the case of complicated expressions the actual calculations 
would be far too involved. It is therefore expedient to make 
use, when possible, of the special form of the integrand to sim- 
plify the work. For example, in order to integrate the expression 

_ it is better to use the substitution t = tana; 

a 2 sin 2 a;+ & 2 cos 2 a; 

instead of that given on p. 237, for sin 2 a; and cos 2 a: can be ex- 
pressed rationally in terms of tana;, and it is therefore unneces- 

sary to go back to t = tan-. The same is true for every expres- 
sion formed rationally from* sin 2 a;, cos 2 as, and sina; cosa;. More- 
over, for the calculation of many integrals a trigonometrical form 
is to be preferred to a rational one, provided that the trigono- 
metrical form can be evaluated by some simple recurrence method. 

* For sin x cos x — tan x cos* x can of course be expressed rationally in terms 
of tan x. 



IV] OTHER CLASSES OF FUNCTIONS 241 

For example, although the integrand in fx n {\/(l — a?)} m dx can 
be reduced to a rational form, it is better to write x = sin u 
and bring it to the form fsin B ucos m+1 udu, since this can easily 
be treated by the recurrence method on p. 222 (or by using the 
addition theorems to reduce the powers of the sine and cosine 
to sines and cosines of multiple angles). 

For the evaluation of the integral 

/ ** , ■ (a 2 + h % >Q), 

•> a cos* + 6 sin* 

instead of referring to the general theory we determine a number A and 
an angle in such a way that 

a = .4 sinG, 6=4cos0; 
that is, we write 

A = Vo> + 6 a , sin G = j, cos 6=2- 
The integral then takes the form 

I f dx 

A J sin(* + 6)' 

and on introducing the new variable * + 6 we find (cf. p. 215) that the 
value of the integral is 

log tan 



Integrate: 

J 1 + ainx J 1 



A e | 2 

Examples 

dx 



+ cos 2 a; 

f dX 8. f dx 
J 1 + cos*" J 3 -)- sin 2 *" 

/dx r 

2 + sin*" 9 - J t* 113 *'**- 

/^- */- 

J sin 3 * J sir 



dx 



sin 3 * J sin* 4- cos* 

K f dx f sin 2 * 4- cos a * . 

/ Z^T' 11 - / s „ : Bmxdx. 

J cos* J 3 C0S 2* -)- su^x 

6- / r- . 12. /V(* 2 -4)i*. 

Jo o + cos* J 



IK798) 



242 THE INTEGRAL CALCULUS [Chap. 

13. fv(l+9x*)dx. 16. J. dx 



14 f dx 17 f^SL 

J (x— 2)V(x i — ix + 3)' J V(l 



Vas + V(l- x) 

V(l + a;) + V(l — x) 



(x- 2)V{x*— ix+ 3) -/ V(l +*)— V(l — x) 
15. / xV(x* + 4x)dx. 18. /— ,, ■ , ;, fe 



dx. 



5. fxV(x* + 4x)dx. l8 ' I i 



+ V(x—a+ 1) 
dx 
V(x—a) + V(x—b) 



19. /"-, 

J V(x— a 



7. Remarks on Functions which are not Integrable 
in Terms of Elementary Functions 

1. Definition of Functions by means of Integrals. Elliptic 
Integrals. 
With the above examples of types of functions which can be 
integrated by reduction to rational functions, we have practi- 
cally exhausted the list of functions which are integrable in 
terms of elementary functions. Attempts to express general 
integrals such as 

f-T, i r 1 ^' f V(°o + a i x + • • • + a n x n )dx 

J VK + a i x + • • • + a«x n ) J 

or I —dx in. terms of elementary functions have always ended 
J x 

in failure; and in the nineteenth century it was finally proved 
that it is actually impossible to carry out these integrations in 
terms of elementary functions. 

If, therefore, the object of the integral calculus were to inte- 
grate functions in terms of elementary functions, we should 
have come to a definite halt. But such a restricted object has 
no intrinsic justification; indeed, it is of a somewhat artificial 
nature. We know that the integral of every continuous function 
exists and is itself a continuous function of the upper limit, and 
this fact has nothing to do with the question whether the integral 
can be expressed in terms of elementary functions or not. The 
distinguishing features of the elementary functions are based on 
the fact that their properties are easily recognized, that their ap- 
plication to numerical problems is often facilitated by convenient 
tables or, as in the case of the rational functions, that they can 
easily be calculated with as great a degree of accuracy as we please. 



IV] NON-INTEGRABLE FUNCTIONS 343 

Where the integral of a function cannot be expressed by 
means of functions with which we are already acquainted, there 
is nothing to hinder us from introducing this integral as a new 
" higher " function in analysis, which really means no more than 
giving it a name. Whether the introduction of such a new func- 
tion is convenient or not depends on the properties whioh it 
possesses, the frequency with which it occurs, and the ease with 
which it can be manipulated in theory and in practice. In this 
sense the process of integration therefore forms a basis for the 
generation of new functions. 

After all, we are already acquainted with this principle 
from our dealings with the elementary functions. Thus we found 
ourselves obliged (p. 167) to introduce the previously unknown 
integral of 1 /z as a new function, which we called the logarithm 
and whose properties we could easily determine. We could have 
introduced the trigonometric functions in a similar way, making 
use only of the rational functions, the process of integration, 
and the process of inversion. For this purpose we need only take 
one or other of the equations 

. f x dt r* dt 
arc tanx = / or arc sina; = / 

■'ol + C Jo V(l - ^ 

as the definition of the function arc tana; or arc sin* respectively, 
in order to arrive at the trigonometric functions by inversion. 
By this process the definition of these functions is separated 
from geometry, but we are naturally left with the task of develop- 
ing their properties, also independently of geometry.* 

The first and most important example which leads us beyond 
the region of elementary functions is given by the elliptic integrals. 
These are integrals in which the integrand is formed in a rational 
way from the variable of integration and the square root of an 
expression of the third or fourth degree. Among these integrals 
the function 

U(s)= I ; 

turns out to be of particular importance. Its inverse function 
s(u) plays a correspondingly important part. In particular, for 

* We shall not go into the development of these ideas here. The essential 
step is to prove the addition theorems for the inverse functions, i.e. for the 
sine and the tangent. 



244 THE INTEGRAL CALCULUS [Chap. 

k = we obtain m(s) = arc sin a; and s(u) = sinw respectively. 
The function s(u) has been as thoroughly examined and tabu- 
lated as the elementary functions. This, however, leads us 
away from the line of the present discussion and into the realm 
of the so-called elliptic functions, which occupy a central position 
in the theory of functions of a complex variable. 

Here we shall merely remark that the name " elliptic inte- 
gral " arises from the fact that such integrals enter into the 
problem of determining the length of an arc of an ellipse. 
(Cf. Chap. V, p. 289.) 

We may further point out that integrals which at first sight have 
quite a different appearance turn out after a simple substitution to be 
elliptic integrals. As an example, the integral 

dx 



I 



V (cos a — cos x) 



is transformed by means of the substitution u = cos - into the integral 

du , 1 

ifc : 



-kV2 f du 

J V(l-u 2 )(l- 



V(l- u 2 )(l- JbV) cos a/2 



dx 



V (cos 2x) 



the integral / 

by means of the substitution u = sin x becomes 

/du 
V(l - u 2 )(l - 2m 2 )' 

and finally the integral / -; ; — 

J V(l — A 2 sin 2 a:) 

is transformed by the substitution u = sin x into 

du 



I 



V(l — M 2 )(l - fc 2 « 2 ) 



2. On Differentiation and Integration. 

Another remark on the relation between differentiation and 
integration may be inserted here. Differentiation may be 
considered a more elementary process than integration, since 
it does not lead us away from the domain of known functions. On 
the other hand, we must remember that the differentiability 
of an arbitrary continuous function is by no means a foregone 
conclusion, but a very stringent additional assumption. We 
have, in fact, seen that there are continuous functions which 



IV] NON-INTEGRABLE FUNCTIONS 245 

are non-differentiable at isolated points, and we may mention 
without proof that since Weierstrass' time many examples have 
been constructed of continuous functions which do not possess 
a derivative anywhere at all.* (There is therefore much less 
in the mathematical definition of continuity than simple intuition 
would lead us to suppose.) In contrast to this, even though in- 
tegration in terms of elementary functions is not always possible, 
in all circumstances we are certain at least that the integral of 
a continuous function exists. 

Taken all in all, we see that integration and differentiation 
cannot be simply classified as more elementary and less elementary, 
but that from some points of view the one and from other points 
of view the other should be thought of as the more elementary. 

In so far as the concept of integral is concerned, we shall see 
in the next section that it is not closely bound up with the 
assumption that the integrand is continuous, but that it may be 
extended to wide classes of functions with discontinuities. 



8. Extension op the Concept of Integral. Improper 
Integrals 

1. Functions with Jump Discontinuities. 

In the first instance we see that there is no difficulty in ex- 
tending the concept of integral to the „. 
case where the function to be in- 
tegrated has jump discontinuities at 
one or more points in the interval 
of integration. For we need only 



take the integral of the function as 

the sum of the integrals over the Fig- 4— The integral of a 

_ . - . 1-1.1 discontinuous function 

separate sub-intervals in which the 

function is continuous, f The integral then retains its intuitive 

meaning as an area (cf. fig. 4). 

*Cf. Titchmarsh, The Theory of Function* (Oxford, 1932), §§ 11-21-11-23 
(pp. 350-354). 

f We should really observe that in our previous definition of integral we 
took the interval as closed and the function as continuous in the closed interval. 
This gives us no trouble, since in each closed sub-interval we can extend the 
function so that it is continuous by taking for the value of the function at the 
end-point the limit of the function as x approaches the end-point from the 
interior of the interval. 



246 THE INTEGRAL CALCULUS [Chap. 

2. Functions with Infinite Discontinuities. 

It is quite a different matter when the function has an infinite 
discontinuity in the interior of the interval or at one of its ends. 
In order even to formulate the notion of integral in this case we 
must introduce a further limiting process. Before stating 
the general definition we shall illustrate some of the possibilities 
by means of examples. 

dx 



We begin with the integral / — , 

J x* 



where a is a positive number. The integrand ljx* becomes infinite as 
x -*• 0, and we therefore cannot extend the integral to the lower limit 0. 
We can, however, try to find what happens when we take the integral 
from the positive limit e to the limit 1, say, and finally let z tend to 0. 
According to the elementary rules of integration, we obtain, provided 
a* 1, 

/• t ^=_l_(l_ el -« ) . 
J, x* 1 - a 

We immediately recognize that the following possibilities occur: (1) a is 
greater than 1; then as e -»• the right-hand side tends to 00 : (2) a is 
less than 1; then the right-hand side tends to the limit 1/(1 — a). In the 
second case, therefore, we shall simply take this limiting value as the 
integral between the limits and 1. In the first case we shall say that 
the integral from to 1 does not exist. (3) In the third case, where a = 1, the 
integral will be equal to — logs and therefore as e -»• it approaches no 
limit, but tends to 00 ; that is, the integral from to I does not exist. 
Another example of the extension of the integral of a function up to an 

infinite discontinuity is given by the integrand — ; ; . We find that 

V (1 — a?) 

r 1 -' dx . ,. . 

aro sin (1 — e). 



I 



'0 v a - **) 

If we let e tend to 0, the right-hand side converges to a definite limit, tc/2; 

/•l tint 

we therefore call this the value of the integral / -7 , even 

Jo v (1 — x 3 ) 
though the integrand becomes infinite at the point x = 1. 

In order to extract a perfectly general concept from these 
examples, we notice in the first place that it clearly makes no 
essential difference whether the discontinuity of the integrand 
lies at the upper end or the lower end of the interval of in- 
tegration. We now make the following statement: 



IV] IMPROPER INTEGRALS 247 

// in an interval a ^ x ^ b the function f(x) is continuous 

' f(x)dx as 

a 



the limit 



lim / f(x) dx 

r — ^.0 •* n 



-O^a 



— where the point b — e approaches the end-point b from the in- 
terior of the interval — provided that such a limit exists. 

In this case we say that the improper integral I f(x)dxccm- 

" a 

verges. If, however, no such limit exists, we say that the integral 
/ f(x)dx does not exist or does not converge or that it diverges. 








Fig. 5. — To illustrate the convergence or divergence of improper integrals 

An analogous definition holds for the case where the lower 
limit of the interval of integration, and not the upper, is the 
exceptional point. 

Even improper integrals can be interpreted as areas. In the first instance, 
of course, there is no sense in speaking of the area of a region which extends 
to infinity; yet one may attempt to define such an area by means of a passage 
to the limit from a bounded region with a finite area. For example, the 
above results for the function \jx°- imply that the area bounded by the 
sr-axis, the line x = 1, the line x — e, and the curve y = lfx* tends to a 
finite limit as e -> 0, provided that a < 1, and that it tends to infinity if 
a Si 1. This fact may be simply expressed as follows: the area between 
the a;-axis, the y-axis, the curve, and the line x = 1 is finite or infinite 
according as a < 1 or a Ji 1. 

Intuition can, of course, give us no precise information about the 
finiteness or infiniteness of the area of a region stretching to infinity. Of 
such a region we can only say that the more closely its sides approach one 
another the more likely it is to have a finite area. In this sense fig. 5 illus- 



248 THE INTEGRAL CALCULUS [Chap. 

trates the fact that for a < 1 the area under our curve remains finite, 
while for a ^ 1 it is infinite. 

In order to find out whether a function /(a;) which has an in- 
finite discontinuity at the point x= b can be integrated up to 
b, we can often save ourselves a special investigation by using 
the following criterion: 

Let the function f(x) be positive* in the interval a ^ x ^ b, 

and let lim f(x) = 00 . Then the integral ff(x) dx converges if there 

exist both a positive number ju. less than 1, and a fixed number 

M independent of x, such that everywhere in the interval 

M 

a<Lx<b the inequality /(a;) ^ is true; in other words, 

(6 — xf 

if at the point x = b the function f (x) becomes infinite of a lower 

order than the first. On the other hand, the integral diverges, 

if there exist both a number v 22 1 and a fixed number N, such 

that everywhere in the interval a ^ x < b the inequality 

f(x) ;> is true; in other words, if at the point x = b 

J K ' - (j _ x y J r 

the function f(x) becomes infinite of the first order at least. 

The proof follows almost immediately by comparison with 

the very simple special case discussed above. In order to prove 

the first part of the theorem we observe that for < e < b — a 

we have 



dx. 



As e -> the integral on the right, which is obtained from the 
integral j— (p. 128) by a simple change of notation, has a limit, 
and therefore remains bounded. Moreover, the values of 
[ f(x)dx increase monotonically as e-»-0; since they are also 

Ja -b 

bounded, they must possess a limit, and the integral J f(x) dx 
therefore converges. 

The parallel proof of the second part of the theorem is left 
as an exercise for the reader. 



* In the Appendix to Chap. VIII (p. 418) we shall see that this restriction 
of sign can easily be removed. 



IV] IMPROPER INTEGRALS 



249 



We likewise see at once that exactly analogous theorems hold 
where the lower limit of the integral is a point of infinite dis- 
continuity. If a point of infinite discontinuity lies in the interior 
of the interval of integration, we merely use this point to 
divide the interval into two sub-intervals and then apply the 
above considerations to each of these separately. 

As a further example we consider the elliptic integral 

\\ dX (P<1). 

Jo V(l — x^il — kV) 

From the identity 1 — x* = (1 — x)(l + x) we see at once that as x -*■ 1 
the integrand becomes infinite only of order \, whence it follows that the 
improper integral exists. 

3. Infinite Interval of Integration. 

Another important extension of the concept of integral 
consists in taking one of the limits of integration as infinite. 
In order to make this extension precise, we introduce the 
following notation: if the integral 

f(x)dx, 



J 



where a is fixed, tends to a definite limit when A increases posi- 
tively beyond all bounds, we denote the limit by 



/ f(x)dx, 

Ja 



and call it the integral from a to 00 of the function f{x). Of 
course such an integral does not necessarily exist or, as we often 
say, converge. 

Simple examples of the various possibilities are again yielded by the 
functions f(x) = 1/a", 

/"J-_L. M w_ 1} . 

Jl x* 1 — a 

Here we see that, if we again exclude the case a = 1, the integral to infinity 
exists for the case a > 1, and in fact 



Jf 



dx 



on the contrary, when a < 1 the integral no longer exists. For the 
case a = 1 the integral again clearly fails to exist, since log* tends to in- 
finity as x does. We see, therefore, that with regard to integration over an 

9* (1798) 



250 THE INTEGRAL CALCULUS [Chap. 

infinite interval the functions l/x* do not behave in the same way as for 
integration up to the origin. This statement also is made plausible by a 
glance at fig. 5, For we see that the larger a is, the more closely do the 
curves draw in towards the r-axis when x is large, so that we can readily 
suppose that the area under consideration tends to a definite limit for 
sufficiently large values of a. 

The following criterion for the existence of an integral with 
an infinite limit is often useful. We again assume that for suffi- 
ciently large values of x, say for x S: a, the integrand has always 
the same sign, which without loss of generality we can choose 
to be positive.* Then we have the following statement: 

/•CO 

The integral / f (x)dx converges if the function f (x) vanishes at 

J a 

infinity to a higher order than the first, that is, if there is a number 

v > 1 such that for all values of x, no matter how large, the 

M 
relation <.f(x) ^ — is true, where M is a fixed number inde- 
x" 

pendent of x. Again, the integral diverges if the function remains 

positive and vanishes at infinity to an order not higher than the 

first, that is, if there is a fixed number N > such that xf(x) S; N. 

The proof of these criteria, which runs exactly parallel to 

the previous argument, can be left to the reader. 

1 — dx(a > 0). The integrand 

a «* 

vanishes at infinity to the second order. As a matter of fact, we see at 

C A 1 11 

once that the integral does converge, for / — dx = , and therefore 

J a x 2 a A 



f 

Ja 



— dx = -. 
3? a 



Another equally simple example is 



f 

Jo 



-dx= lim (arc tan.4 — arc tan 0) = 



Jo 1 + a; 2 a->* 2 

i. The Gamma Function. 

A further example of particular importance in analysis is 
offered by the so-called gamma function 






l dx (n>0). 



• As we shall see in the Appendix to Chap. VIII (p. 418), this restriction 
of Bign can easily be removed. 



IV] IMPROPER INTEGRALS 251 

Here also the criterion of convergence is satisfied; e.g. if we 

choose v = 2, we have lima;'' . e~ <c x n ~ x = 0, since the expo- 
se— >-» 
nential function e~" tends to zero to a higher order than any 
power 1/a;"* (m > 0). This gamma function, which we can think 
of as a function of the number n (not necessarily an integer), 
satisfies a remarkable relation, which we can arrive at in the 
following way by integration by parts. To begin with, we have 

f(T*x n - 1 dx = — e-*x n ~ x + (» — l)fe- x x n - 2 dx. 

If we take this formula between the limits and A and then 
let A increase beyond all bounds, we immediately obtain 

r» = (n — 1) Ce-*x n -*&x = (n — l)F(n — 1), 
Jo 

and by this recurrence formula, provided /x is an integer and 
< n < n, 

T(n) = (n — 1) (n — 2) . . . (w — p.) f e-'x n -> L - 1 dx. 

Jo 

In particular, if w is a positive integer, we have 

r(w) = (n — l)(n - 2) . . . 3 . 2 . 1 f e~*dx, 

Jo 

r°° 

and since / e~*dx = 1, 

•'0 

it follows finally that 

r» = (n — l)(ra — 2) . . . 2 . 1 = (» — 1)! 

This expression of a factorial by an integral is of importance 
in many applications. 



The integrals / e-*' dx, J a"*-** dx 

Jo Jo 



also converge, as we may easily convince ourselves by means of our 
criterion. 

5. The Dirichlet Integral. 

A convergent integral, important in many applications, 
whose convergence does not follow directly from our criterion, 
and which is a simple case of a type investigated by Dirichlet, is 



i=r s ™dx. 

Jo X 



252 THE INTEGRAL CALCULUS [Chap. 

This integral is easily seen to be convergent if the upper limit 

is finite, for -*■ 1 as x -*■ 0. Its convergence in the infinite 

interval is due to the periodic change of sign of the integrand, 
which causes the contributions to the integral from neighbour- 
ing intervals of length -n almost to cancel one another. In order 
to make use of this fact we write the expression 



in the form 



„ psinas. 
Dab = / dx 

•>A X 



^"•""sina:, f B+,r sina; 7 , ^'siat 



= fSmx dx __ fSmx dx fSmt 
Ja x Jb x Ja+k t 

introduce in the last of the three integrals on the right the new 
variable x=t — v, whence sini = — since, and obtain 

r^+'g^x r B+ "smXj r B sina; , 
D AB = / ax — i ax — / ax. 

J A X J B X J A X-\- IT 

Addition of this to the original expression for D AB gives us 

/-*+«• sin a, r B+ *smx, , r B sina; , 

2JJ AB = I ax — / ax-\- tt\ ax. 

Ja x j b x Ja x(x-\- it) 



s(a; + ff) 

Prom this it follows, if we assume that B > A > 0, that 

2tt , r B dx 
x*'' 



\2DAB\< 2 i+«f A E 



for we may nse the method of p. 127, observing that 



1 < sina; < 1 
x x ~ x 



, 1 sina; 

and = S> 



x 2 x (x + 77) x 2 

for positive values of x. The integral on the right is conver- 
gent, by our criterion, and our formula shows that | D AB I -*■ 
as A and B both tend to infinity. Now 

I A)B Doa I = I Dab |> 

and it follows from Cauchy's convergence test that D 0B tends 
to a definite limit as B -> 00. In other words, the integral I 



253 



IV J IMPROPER INTEGRALS 

exists. Another proof of this is given in the Appendix to Chap. 
VIII (p. 418), and on p. 450 we shall further show that I has the 
value 7t/2. 

6. Substitution. 

It is obvious that all rules for the substitution of new variables, 
&c, remain valid for convergent improper integrals. As an 

example, in order to calculate J xe~**dx we introduce the new 
variable u = x 2 and obtain ° 

/ xe-^dx = ^ / e -"du = lim - (1 — e~ A ) = - 

Another example of the use of substitution in the investigation 
of improper integrals is given by the Fresnel integrals, which 
occur in the theory of diffraction of light: 

Fi=J o sm(a5 2 )<fc, F 2 =fcoa(a?)dx. 

The substitution x 2 = u yields 

Fl =\r^ du , F,=ir™*. 

Integrating by parts, we have 

r B sinw du = cos .4 _ cosg _ 1 /- B cosw , 

As A and B tend to <» the first two terms on the right tend to 
0, and by the criterion of p. 250 the integral also tends to 0. 
Hence by the same argument as for the Dirichlet integral we see 
that the integral F t converges. The convergence of the integral 
F 2 is proved in exactly the same way. 

These Fresnel integrals show that an improper integral may 
exist even although the integrand does not tend to zero as x -+ oo . 
In fact, an improper integral can exist even when the integrand 
is unbounded, as is shown by the example 

.00 

/ 2u coa (u*)du. 
When u l = nn, i.e. when w = Vw, n = 0, 1, 2, . . . , the in- 



a 5 4 THE INTEGRAL CALCULUS [Chap. 

fcegrand becomes 2V ntt cos rnr = +2Vn77, so that the integrand 
is unbounded. By the substitution w 2 — x, however, the integral 
is reduced to 

/ cos(a; 2 )&, 
Jo 

yhich we have just shown to be convergent. 

By means of a substitution an improper integral may often 
be transformed into a proper one. For example, the transfor- 
mation x = sin u gives 

r 1 dx r'j * 

•A) ^(1 — x 2 ) J o 2 

On the other hand, integrals of continuous functions may be 
transformed into improper integrals; this occurs if the trans- 
formation u = <f> (x) is such that at the end of the interval of 
integration the derivative <£'(«) vanishes, so that dxjdu is infinite. 

Examples 



Test the convergence of the improper integrals in Ex. 1-11: 

i. r 3 ^ 2 . f 1 *l % 3- /•• _&_ 

J-B x" J-i -tyx ./_„ 1 + x* 

1"° dx r" dx 

J (1 + x)Vx' J 1 — cos x 

f B dx 

6. / =, where Oj, o 2 , a a , a t are 

J a V(x— a^(x — a 2 )(x — a z ){x — a 4 ) 

all difierent and lie between A and B. 

„ r m arc tan x , „ r x arc tan x , 

7. / — dx. 8. / -ax. 

i 1+J^ J 1-x* 

' — dx. 10. / — dx. 11. / log t&nxdx. 

1 1 - e* J e* - 1 Jo 

12.* Prove that / sin* it ( x + - ) \dx does not exist. 

13.* Prove that lim f° — ^— = 0. 

*->■ J 1 + hx w 

X* X^ — ^ /*00 gjji 3. 
rfa;, (6) / dx conver- 
se, - * + * •'O ** 

15.* Does / dt converge? 

Jo 1 + t 



IV] IMPROPER INTEGRALS 355 

16.* (a) If a is a fixed positive number, prove that 



lim / dx = 7t. 



(6) If f(x) is continuous in the interval -lgigl, prove that 
h 



lim f 1 



h* + x* 



f(x) dx = tc/(0). 



Miscellaneous Examples 
Evaluate the integrals in Ex. 1-7: 

1. I e* lcsiax dx. 

2. I Bin 3 xcoa*xdx. (By a shorter method than that of the text, 
using trigonometrical identities.) 

3. [(logxfdx. 4. [ ***?" . 5. [Vl-e-^dx. 

6. f xe-*'*™'*dx. 7. r 2 - sin (a; - -) dx. 

8.* Prove that lim <r*' f*e*'dt = 0. 
*— >*> Jo 

9. Assuming that | a | 4= | P l> prove that 

1 r T 
lim — / sin otx sin $x dx — 0. 



r.7 

/o 
10. Evaluate / ~ a?er<* cos2a:<fo;. 



1 f x*er-»'< 



11.* Prove that the substitution x = — i-?, where cc8 — yp 4= 0, 
transforms the integral ^ 



./ Vaa: 4 - 



<fa 



Voa; 4 + bx 3 + ex 2 + dx + e 

into an integral of similar type; and that if the biquadratic 

ax* + bx* + ex* + dx + e 

has no repeated factors, neither has the new biquadratic in t which takes 
its place. 

Prove that the same statements are true for 

fB(x, Vox* + bx 3 + ex 1 + dx + e)dx, 
where ij is a rational function. 



256 THE INTEGRAL CALCULUS [Chap. 

12. Find the limit as n -*■ co of a n = — — -\ — - +... + —. 

n + 1 » + 2 2m 

13* Find the limit of 



V»» — Vn 1 — 1 Vn* — 4 V» s — (» — l) 3 



14.* Prove that lim 



"Inl 1 



15.* If a is any real number greater than — 1, evaluate 

.. 1" + 2« + 3* + . . . + W 
liro 



»+i 



Appendix to Chapter IV 

The Second Mean Value Theorem of the Integral 
Calculus 

The method of integration by parts affords us an easy method 
for proving an important theorem on the estimation of integrals, 
usually called the second mean value theorem of the integral 
calculus. 

Let us suppose that the function <f>(x) is monotonic and con- 
tinuous in the interval a^x^b, and that the derivative <f>'(x) 
is continuous; and let us further suppose that/(x) is an arbitrary 
function continuous in the same interval. Then the second mean 
value theorem of the integral calculus is expressed as follows. 
There exists a number £ , such that a ^ | ^ b, for which 

fj(x) <j>(x)dx=<f> (a) jj{x) dx+<f> (b) f ( "f(x) dx. 

To prove this we notice first that we can assume that 
<f>(b) = 0; for replacing </>(x) by <f>(x) — <f>(b) changes both sides 
of the equation by the same amount, and gives us a function 
which vanishes at x = b. Moreover, we can assume that 
<j>(a) > 0; for if <f>(a) < we need only replace ^>(x) by — (f>[x), 
which changes the sign of both sides of the equation. (The case 
^(a) = is trivial; for if both (f>(a) and <f>(b) vanish, <f>(x) must be 
identically zero, and our equation becomes = 0.) We therefore 



IV] SECOND MEAN VALUE THEOREM 257 

need only prove that if <f>(x) is continuous and monotonic de- 
creasing, and <£(&) = 0, then 

J f(x)<j} (x) dx= <f> (a) f f(x) dx. 

We now put F(x) = / f(x)dx and apply the formula foi 

integration by parts to the left-hand side of the last equation; 
we then have 

\f(x) <j>(x)dx=F(x)<f>(x)\ + f F (x) {—<f>'(x) } dx. 

Ja \ a Ja 

The integrated part vanishes, since F(a) and <£(&) are zero. The 
expression — <f>'(x) is everywhere positive, so that we can apply 
the first mean value theorem of the integral calculus. We thus 
find that the integral on the right has the value 

F(£) £{-*' (*)} dx > a^i^b. 

But 

F{$) = f f(x)dx and f {— <f>' {x)}dx = 0(a) — 0(6) = <j>(a) 

and our theorem is established. 

This theorem can be extended (although we shall not carry 
out the proof) to more general classes of functions. For the theorem 
remains true for all continuous monotonic functions <£(:r), whether 
they have derivatives or not. In fact, it is true for any discon- 
tinuous monotonic function for which we are in a position to 
integrate f(x) <f> (x). 



CHAPTER V 
Applications 

In this chapter, after disposing of a few preliminaries, we 
shall illustrate how what we have now learned may be applied 
in a great variety of ways in geometry and physics. 

1. Eepresentation of Curves 
1. Parametric Representation. 

As we saw in Chap. I (p. 17), in representing a curve by means 
of an equation y = f(x) we must always restrict ourselves to a 
single- valued branch. Hence it is often more convenient — when 
we are dealing with a closed curve, in particular — to introduce 
other analytical methods of representation. The most general 
and at the same time the most useful representation of a curve 
is parametric representation. Instead of considering one of the 
rectangular co-ordinates as a function of the other, we think of 
both the co-ordinates x and y as functions of a third independent 
variable, a so-called parameter; the point with the co-ordinates 
x and y then describes the curve as t traverses a definite interval. 
Such parametric representations have already been encountered. 
For example, for the circle x 2 + y 2 = a 2 we obtain a parametric 
representation in the form x = a cost, y=asin.t. Here, as we 
already know, t has the geometrical meaning of an angle at the 
centre of the circle. For the ellipse a; 2 /a 2 + y 2 /b 2 == 1 we like- 
wise have the parametric representation x = a cost, y= b smt, 
where t is the so-called eccentric angle, that is, the angle at 
the centre corresponding to the point of the circumscribed circle 
lying vertically above or below the point P(a cost, bsint) of 
the ellipse (fig. 1). In both these cases the point with the co- 
ordinates x, y describes the complete circle or ellipse as the 
parameter t traverses the interval from to 2tt. 

258 



[Chap. V] PARAMETRIC REPRESENTATION 



259 



In general, we can seek to represent a curve parametrically 
by taking 

that is, by considering two functions of a parameter t ; the shorter 
notation x(t) and y(t) will henceforth be used where there is no 
danger of confusion. For a given curve these two functions 
<j>(t) and tfi(t) must be determined in such a way that the totality 
of pairs of functional values x(t) and y(t) corresponding to a given 
interval of values of t gives all the points on the curve and no 
points that are not on the curve. If a curve is in the first 
instance given in the form 
y—f(x), we can arrive at a 
representation of this kind by 
first writing x = <f>(t), where 
<f>(t) is any continuous mono- 
tonic function which in a 
definite interval passes exactly 
once through each of the values 
of a; in question; it then follows 
that y=f{<f>(t)}, that is, the 
second function ip(t) is deter- 
mined by compounding/ and <f>. 
We thus see that owing to the 
arbitrariness in the choice of the function cf> we have a great 
deal of freedom in representing a given curve parametrically; 
in particular, we may actually take t = x and may thus think 
of the original representation y=f(x) as a parametric repre- 
sentation with the parameter t = x. 

The advantage of the parametric representation is that this arbitrari- 
ness may be utilized for purposes of simplification. For example, we repre- 
sent the curve y = -y/i 8 by taking x = P, y — t l , so that ip(t) = f, 
ty(t) = t s . The point with the co-ordinates x, y will then describe the whole 
curve (semicubical parabola) as t varies from — 00 to +00. 

If, on the other hand, a curve is originally given by a para- 
metric representation x = <f>(t), y = tfi(t), and we wish to obtain 
the equation of the curve in non-parametric form, that is, in the 
form y = f(x), we have only to eliminate the parameter t from 
the two equations. In the case of the parametric representations 
of the circle and ellipse given above we can do this at once h\ 




Fig. I 



260 APPLICATIONS [Chap. 

squaring and using the equation sin 2 * + cos 2 * = 1. (For a further 
example see below.) In general, we should have to find an expres- 
sion for t from the equation x = <f>(t) by means of the inverse 
function t = <J>(a;) and substitute this in y = tfi(t), in order to 
obtain the representation* y = ^t{0(a;)}=/(a;). In such an 
elimination, of course, we must ordinarily restrict ourselves to 
a portion of the curve; in fact, to a portion which is not cut 
twice by any line parallel to the y-axis. 

The parametric representation has associated with it a de- 
finite sense in which the curve is described, corresponding to the 
direction in which the values of the parameter increase; this 
direction we shall call the positive sense. If, for example, the 
point x = x(t), y — y(t) describes a curve G as t traverses an 
interval t ^ t ^ ^ and the end-points P and P 1 of the curve 
correspond respectively to * and t v then the curve is traversed 
positively in the direction from P to P v If we introduce t = — t 
as a new parameter, the curve C will correspond to the values 
— ^ ^ t ^ — t of the variable t, and the points P and P x 
will correspond to t = — 1 and t = — ty respectively. If we 
now traverse the curve from P to P ± we proceed in the direction 
in which the values of the parameter t decrease, that is, in the 
negative sense. In general, a change of parameter t = t(r) pre- 
serves the sense in which the curve is described if the function 
t(r) is monotonic increasing, but reverses it if the function t[r) 
is monotonic decreasing. 

2. Interpretation of the Parameter. Change of Parameter. 

In many cases we can give an immediate physical interpre- 
tation to the parameter t, namely, time. Any motion of a point 
in the plane may be expressed mathematically by the fact that 
the co-ordinates x and y appear as functions of the time. These 
two functions therefore determine the motion along a path or 
trajectory in parametric form. 

As an example of this we have the cycloids which arise when a circle 
rolls along a straight line or another circle. Here we limit ourselves to 
the simplest case, in which a circle of radius a rolls along the ai-axis, and 

* It may happen, however, that the equation y — f(x) obtained in this way 
represents more than the original parametric representation. Thus for example 
the equations x = a sin t, y ■= b sin t represent only the finite portion of the 
line y — bx/a lying between the points x — —a, y — —b and x = o, y — b, 
whereas the equation y — bxla represents the whole of the line. 



V] 



PARAMETRIC REPRESENTATION 



261 



we consider a point on its circumference. This point then describes a 
" common " cycloid. If we choose the origin of the co-ordinate system 
and the initial time in such a way that for time t = the corresponding 
point of the curve coincides with the origin, we obtain (cf. fig. 2) the 
parametric representation 

x = a(t — sin<), y = o(l — cos*) 

for the cycloid; here t denotes the angle through which the circle has 
turned from its original position; in the case where the velocity of 
rolling is uniform it is proportional to the time. 




Fig. 2. — Cycloid 



By eliminating the parameter t we can obtain the equation of the curve 
in non-parametrio form, at the cost, however, of neatness of expression. 
We have 



a — « . 
cost = -, t = arc cos 



«^-.,_ ± ^i-(-iE}, 



and hence 



x = a arc cos - =F V {{2a — y)y), 

a 



thus obtaining x as a function of y. 

In the parametric representation of a given curve we have a 
great deal of freedom in the choice of parameter (p. 259). For 
example, instead of the time t we could take the quantity 
r = ft as parameter, or indeed any arbitrary quantity t which 
is related to the original parameter t by an arbitrary equation 
of the form t = w(t), where we assume that for the whole interval 
of values of t considered this function has a unique inverse t = k(t). 
If increasing values of t correspond to increasing values of t, 
the positive sense of description remains the same; otherwise 
it is reversed. 

Parametric representation is, of course, not limited to rect- 
angular co-ordinates, e.g. it can just as well be used with the 
polar co-ordinates r and 6, which are connected with the rect- 
angular co-ordinates by the well-known equations a;=rcos#, 



262 



APPLICATIONS 



[Chap. 



y= r sin 5, or r = \/(3? + y z ), sin<?= y/r, cos#= xjr; the equations 
of the curve would then be r = r(t), 8 = 6(t). 

As an example, the straight line may be represented parametrically 




(see fig. 3) in the form 



cos< 



6= a + t 



(p and a. being constants), from which we 
immediately obtain the equation of the 
line in polar co-ordinates, 

P 



Fig. 3 



cos (9 — a) 
by eliminating the parameter t. 



3. The Derivatives for a Curve Represented Parametrically. 

If on the one hand a curve is given by an equation y =/(#), 
and on the other hand it is given parametrically by x = x(t), 
V = y(0> * nen we must have y(t) = f{x(t)}. By the chain 
rule for differentiation it follows that 



or 



dy 
dt' 


dy dx 
dx dt 


y' = 


,<h = y 

dx x 



where as an abbreviation for differentiation with respect to the 
parameter t we use a dot over the variable (Newton's notation), 
instead of the dash '; the latter we shall reserve for differen- 
tiation with respect to x. 

For the oyoloid, for example, we have 

t 

A ■= a(l — coat) = 2a sin 8 -, 

i) = a shut = 2a sin - cos -. 
2 2 



These formnlse show that the cycloid has a cusp with a vertical tangent 
at the points t = 0, ±27t, ±4rt, ... at which it meets the z-axis, for on 
approaching these points the derivative y 1 = #/as — cot(</2) becomes 
infinite. At these points y is equal to 0; everywhere else y > 0. 



V] 



PARAMETRIC REPRESENTATION 



263 



The equation of the tangent to the curve is 

(£ — x)y — (v — y)* = 0, 

where g and rj are the "current" co-ordinates, that is, the 
variable co-ordinates corresponding to an arbitrary point on the 
tangent. For the equation of the normal, i.e. the straight line 
through a point of the curve perpendicular to the tangent at 
that point, we likewise obtain 

(£— x)x + ( v — y)y=0. 

The direction cosines of the tangent, that is, the cosines of the 
angles a, /? which the tangent makes with the x and y axes 
respectively, are given by the expressions 



cos a = 



±V(* 2 + y z ) 



cos)8 = 



y 



±V(* 2 + f)' 



as we may verify by elementary methods. The corresponding 
direction cosines of the normal are given by 



cos a = 



-y ™ff- x 



(See fig. 4.) 

These formulae show us that at every point at which & and y 
are continuous and x 2 + y 2 4= the direction of the tangent 
varies continuously with t. This is 
the most important case for us; it 
is interesting, however, to illustrate 
by examples the various possibilities 
that arise when our assumptions are 
not fulfilled and we cannot state 
directly that the tangent keeps on 
turning continuously. At a point at 
which x = y = the tangent may 
or may not turn continuously. 
As one example we have the curve 
x = t s , y = t 2 discussed on pp. 99, 
259, which has a cusp at the origin 
even though x and y are continuous everywhere. As 
another example we consider the curve x = 1?, y = i 8 , which is 
the straight line y = x. This curve has the same tangent direc- 




Fig. 4. — Direction cosines of the 
tangent and the normal 



364 APPLICATIONS [Chap- 

tion everywhere; the latter is therefore continuous, although 
the derivatives x and y both vanish for t = 0. Moreover, at a 
point at which x and y are discontinuous the direction of the 
tangent may or may not be continuous. For let </>(t) be any 
continuous monotonic increasing function, denned for t x ^ t ^ t % , 
which has a sharp corner at t — t z , t^ <t z <.t 2 . Then the curve 
* = t> y = 4(t)> which is the same curve as y — <f>(x), has a sharp 
corner at x = t z ; while the curve x = <f>(t), y = <f>(t), which is a 
segment of the straight line y = a;, has a constant tangent direction, 
even though the derivatives x and y do not exist at t = t 3 . This 
indicates that if we wish to investigate the behaviour of the 
tangent at a point where our theorem does not apply, we should 
first use the formulae to find cos a or cosjS as functions of t and 
then investigate these direction cosines themselves. 

From a well-known formula in trigonometry or analytical 
geometry we find that the angle between the two curves repre- 
sented parametrically by x = x 1 (t), y=y\ (t) and x== x 2 (t), 
y—Vi (0 respectively (that is, the angle between their tangents 
or normals) is given by the expression 

cosS = - *A + ft& . 

±V(*l 2 +y 1 2 )V(*2 2 +2/2 2 ) 

The indeterminacy of the signs of the square roots in the 

last few formulae suggests that the angles are not completely 

determined, since we can still specify either sense of direction on 

the tangent or normal as " positive ". Taking the square root 

as positive, as is usually done, corresponds to choosing for the 

positive direction on the tangent the direction in which the 

parameter increases, and for the positive direction on the normal 

the direction obtained by rotating the tangent through an angle 

7r/2 in the positive * sense. 

d?v 
The second derivative y" = — " is obtained in the following 

CLX 

way by means of the chain rule and the rule for differentiating 
a quotient: 

v " = ^L = ^ — = - (t\ \ = *$ ~ y* I 
dx dt dx dt \x/ x a? £ 

* I.e. in the counter-clockwise sense. 



V] PARAMETRIC REPRESENTATION 265 

whence 

«" = *k = £ y—y £ 

y dx* x* ' 

4. Change of Axes for Curves Represented Parametrically. 

If we rotate the axes through an angle a in the positive direc- 
tion, the new rectangular co-ordinates |, rj and the old ones 
x, y are related by the equations 

x= |cosa — 17 sina, £= a;cosa-{- y sina, 
y = |sina + -q cosa, 17 = — a; sina + y cosa. 

Thus the new co-ordinates £ and 17 are specified along with x and 
y as functions of the parameter t. By differentiation we at once 
obtain 

£ = £ cosa — 1) sina, £ = a cosa -f- y sina, 
y = £ sina -f- 17 cosa, r;= — jc sina + y cosa. 

Let us suppose that the curve is given in polar co-ordinates 
and that both polar co-ordinates and rectangular co-ordinates 
are given as functions of a parameter t. Then by differentiation 
with respect to t we obtain from the equations a;=rcos0, 
y = r sin 6 the formulae 

a5=rcos0 — rsin0.0, ) . s 

. f . . . (o) 

y = f sin<?-}- r cos0 . 8, > 

which are frequently used in passing from rectangular co-or- 
dinates to polar. As an example we consider the polar equation 
of a curve, r = /(#), which might, for example, arise from a para- 
metric representation r = r(t), d = 6(t) by elimination of the 
parameter t. The angle ift between the radius vector to a point 
on the curve and the tangent to the curve at that point is 
then given by 

We can convince ourselves of this in the following way. If we 
think of the curve as given by an equation y = F(x) and use 6 
as parameter, so that 0=1 and r =f'(0), we have 

, v f tan 6 + r 

tana = w = - = -— 

x f — rtan0 



266 



APPLICATIONS 



[Chap. 



(cf. fig. 5 and equations (a) above). In addition, ifi — a — 0, 

and hence 

_ y 1 — tan 9 _ r + f tan 2 6 _ r 
~~ 1 + y'tsmO ~ r+ rtan 2 ~~ r 

H 



tan^r ■■ 




Fig. s 



This formula can also be established by geometrical methods. 



5. General Remarks. 

In discussing given curves we sometimes consider properties 
which do not assert anything about the form of the curve 
itself, but merely something about the position of the curve 
with respect to the co-ordinate system; for example, the occur- 
rence of a horizontal tangent, expressed by the equation y = 0, 
or the occurrence of a vertical tangent, expressed by x = 0. 
Such properties do not persist when the axes are rotated. 

In contrast to this, a point of inflection will still be a point 
of inflection after the axes have been rotated. According to the 
formula on p. 265 the condition for a point of inflection is 

xy — xy = 0. 

If on the left we replace the expressions A, y, if, y' by their values 
in terms of the new co-ordinates f , rj, we readily obtain 

xy — xy = £j — £rj . 

Hence from the equation xy — xy = it follows that £77 — £17 = 0, 
so that our equation expresses a property of the point of the 
ourve which is independent of the co-ordinate system. 

We shall often see later that properties which are truly 
geometrical are expressed by formulae which are unaltered in 
form by rotation of the axes. 



V] PARAMETRIC REPRESENTATION 267 

Examples 

1. Find the equation, in non-parametric form, of the curve 

x = acos28 cos 6 
y = a cos 26 sin 6. 

2. A oirole 0, of radius r, rolls on the outside of a fixed circle of radius 
B. The point P on the circumference of e moves with c, and describes a 
curve called the epicycloid. Find the parametrio representation of the 
epicycloid (consider c to rotate with constant velocity, and measure time 
so that at t = the point P is in contact with the circle O). 

3. Sketch the epicycloid for the special case r = B, and find its para- 
metric equations. (This particular epicycloid is called the cardioid.) 

4. If in Ex. 2 the radius r is less than JJ and c rolls inside O, the point 
P describes a hypocycloid. Find its parametric equations. 

5. Sketch the hypocycloid (1) for B — 2r, (2) for B = Zr. 

6. Sketch the hypocycloid for B = Ar (the astroid) and find its non- 
parametric equation. 

7. Find the parametrio equations for the curve X s + y* = 3axy (the 
folium of Descartes), choosing as parameter t the tangent of the angle 
between the z-axis and the radius vector from the origin to the point 
(*. y)- 

8. Find the formula for the angle a between two curves r = /(0) and 
r = 0(8) in polar co-ordinates. 

9. Find the equation of the curves which everywhere intersect the 
straight lines through the origin at the same angle a. 

10. Let G be a fixed curve and P a fixed point with co-ordinates x , y . 
The pedal curve of O with respect to P is defined to be the locus of the foot 
of the perpendioular from P on the tangent to C. Find the parametric 
representation of the pedal of C if is itself given parametrically by 
x = f(t),y^g(f). 

11. Find the pedal curve of the circle 0, (a) with respect to its centre M , 
(6) with respect to a point P on its circumference. 

12. Find the pedal curve of the ellipse x = a cos 6, y = b sin 8 with 
respect to the origin. 

2. Applications to the Theory ov Plane Curves 

We shall consider two different kinds of geometrical proper- 
ties or quantities associated with curves. The first type consists 
of properties or quantities which depend only on the behaviour 
of the curve in the small, i.e. in the immediate neighbourhood of 
a point, and which can be expressed analytically by means of the 
derivative at the point. Properties of the second type depend on 



268 APPLICATIONS [Chap. 

the whole course of the curve or of a portion of the curve, and are 
expressed analytically by means of the concept of integral. We 
shall begin by considering properties of the second type. 

1. Orientation of Areas. 

The idea of area was our starting-point for the definition of 
the integral; but the connexion between definite integral and 
area is still somewhat incomplete. The areas with which we are 
concerned in geometry are bounded by given closed curves; on 

f{x)dx is 

bounded only in part by the given curve y = /(»), the rest of the 
boundary consisting of lines which depend on the choice of the 
co-ordinate system. If we wished to determine the area interior 
to a closed curve, such as a circle or ellipse, by means of integrals 
of this type, we should have to use some such device as breaking 
up the area into several parts, each of which is bounded by a 
single- valued branch of the curve and also by the as-axis and the 
corresponding ordinates. 

For the discussion of this general case it is convenient first 
to make some remarks on the determination of the sign of the 
area considered. For any surface bounded by an arbitrary 
closed curve which does not intersect itself, we can relate the 
sign of the area to the purely geometrical idea of the sense in 
which the curve is described, according to the following con- 
vention. We say that the boundary of a region is described in 
the positive sense if we go round the boundary in such a direction 
that the interior of the region is on the left;* the opposite sense 
we call negative. If then we consider a region whose boundary 
is traversed in an assigned sense, a so-called oriented region, we 
reckon the area as positive if this sense is positive, and negative 
if this sense is negative (cf. fig. 6). 

Suppose, in particular, that in the interval a ^ x ^ b the 
function f{x) is everywhere positive. We consider the closed 
curve obtained by starting at the point x = b = x lt y = 0, 
traversing the a>axis back to the point x = a = x , y = 0, then 

* If we wish to avoid the words " right " and " left " in such a context, 
we say that the triangle, whose vertices in order are the origin, the point x — 1, 
y = 0, and the point x = 0, y ** 1, is described in the positive sense if the 
vertices are passed in the order mentioned. For every other region, we say 
that the boundary is positively described if it ia described in the same sense 
as this triangle; otherwise it is negatively described. 



V] 



THEORY OF PLANE CURVES 



269 



proceeding along the ordinate to the curve y = f{x), then along 
this curve to the ordinate x = b, and finally along this ordinate 
to the x-axis (cf. fig. 7). The absolute value of the area interior 
to this curve — the number of square units contained in it — is, 

as we know, / f(x)dx. Hence, denoting by A^ the area with 

its sign as determined above, the integral gives us the value A 01 
except for sign. To determine the sign we need only observe 

n 



n 




X, 



Fig. 6. — A positive area 



Fig. 1 



that the boundary of the region is traversed in the negative 
sense, so that A 01 is negative; hence we have 

A 01 = — / f(x)dx. 

"a 

Similarly, if a > b, we find that according to our convention 
A 01 is positive, while the integral / f(x) dx is negative; hence 
in either case A^ is given by the above equation. 

2. The General Formula for the Area as an Integral. 

After these preliminaries, the difficulties mentioned at the 
beginning can now be avoided in a simple way by representing 
our curve parametrically. If we introduce t formally as a new 
independent variable in the above integral, writing x = x (t), 
V = y W =f{ x (0}» w e have 



4>i =-/V (*)*(«)*, 



where t and ^ are the values of the parameter corresponding to 
the abscissse x = a and a^ = b respectively. Here we suppose 
that the branch in question of the curve y —f(x) is related to 



370 



APPLICATIONS 



[Chap. 



an interval t g t ^ t± by a(l, 1) correspondence,* that f(x) is 
everywhere positive, and that x (t) never vanishes in this interval. 
As we have seen, our expression then gives us the area of the 
region bounded by the curve, the lines x =*= a and x = b, and 
the a;-axis. It is, of course, still subject to the disadvantages 
mentioned above. We shall now show that if the curve x = 
x (t)> H=y (*)> *o ^ ' Sa h> i s a closed curve bounding a region 
of area A 01 , the area A 01 is given by an integral which in form 
is exactly the same as the preceding. 

Let us then consider a closed curve which is represented para- 
metrically by the equations x== x(t), y = y{t), the curve being 




B A B 

Fig. 8. — Area of a closed curve 



A 



described just once as t describes the interval t ^ t 5g t v 
In order that the curve may be closed it is essential that 
x(t ) = x(t±) and y(t ) = y{t-j). We shall assume that the deri- 
vatives are continuous except for a finite number of jump-dis- 
continuities at most, and that x 2 + y z is different from zero 
except perhaps at a finite number of points which may be 
corners f of the curve. 

We shall first consider a closed curve which has no corners 
and is convex and of such a type that no straight line intersects 
it in more than two points. We denote by P x and P 2 the points 
at which the curve possesses a vertical tangent; these tangents 
are said to be " lines of support " at P x and P 2 respectively, 
because the points of the curve in the neighbourhood of P 2 and 
P 2 lie entirely on one side of the line. We can then (cf. fig. 8) 

* I.e. is such that every point of it corresponds to a single value of t in the 
interval < £ t S t v and conversely. 

t A continuous curve x — x(t), y — y(t) is said to have a corner at t ■= t if 
the positive direction of the tangent approaches a limit as (t — <„)-* through 
positive values, and approaches a limit as (( — t ) -*■ through negative values, 
but the two limits are not the same. 



V] THEORY OF PLANE CURVES 271 

regard the area bounded by the curve as the sum of the area A 12 
bounded by the closed curve P X MP 2 ABP X , formed as in the pre- 
ceding section, and the area A 21 bounded by the closed curve 
P^NP^AP^. Here we assume that the curve is described in 
the positive sense, as in the figure; by our sign convention A n 
is then positive and A a negative. We suppose that the point 
x (t), y{t) describes the upper part of the curve from P 1 to P 2 as 
t goes from t to t, and the lower part from P 2 to P x as t goes from 
t to t v We then immediately obtain 

A ia =-f y(t)x(t)dt 

and A il =-f' l y(t)x(t)dt; 

hence, for the total area bounded by the convex curve, we have 

Mi 

A=— y(t)x(t)dt. 
J t, 

If we denote by " absolute area " of a region the number of 
square units contained in it— which is, of course, never negative 
— then the above expression always gives us the absolute area 
bounded by the curve, except perhaps for sign. In order to see 
what happens when we reverse the sense in which the curve is 
described, we simply take the same integral from ^ to t instead 
of from t to < x ; our integral becomes 

— / yxdr, 

which is equal to —A. We thus recognize the truth of the follow- 
ing statement: 

The area represented by our formula is positive or negative, 
according as the sense in which the boundary is described is positive 
or negative.* 

* In drawing the figure we have assumed that y > f or all points of the 
curve. This really does not restrict the generality of the result. For if we dis- 
place the curve through a distance a parallel to the y-axis, without rotating it, 
in other words, replace y by y + a, the area is unchanged; the value of the 
integral is likewise unaltered, for the above integral is replaced by 

- f "' (y + a)x(t)dt, 
•>t, 
and since the curve is closed 

f'axdt = a{x(t x ) - x(t„)\ = 0. 



272 



APPLICATIONS 



[Chap. 



Two simple observations enable us to extend our results. 
Firstly, our formula remains valid for closed curves which do 
not intersect themselves, even when they are not convex, but 
have a more general form as illustrated in fig. 9. Secondly, 
the derivatives may have jump discontinuities or may both 
vanish at a finite number of points, which may represent 
corners; according to Chap. IV, § 8, p. 245, the function yx 
remains integrable. (The ordinate to a corner-point is considered 
to be a line of support if the curve in the neighbourhood of the 
point lies entirely to one side of the ordinate). We assume that 
the curve has only a finite number of lines of support, corre- 
sponding to the points P x , P 2 , . . . , P„, and we subdivide the 




Fig. 9 



curve into the single-valued branches P X P 2 , ■ . ■ , P n -iP n > P n Pi- 
Then as in fig. 9 we obtain the area bounded by the curve 
in the form A = A Xi + A 23 + . . . + A n - X , „ + A nl . (See 
fig. 9, which illustrates this for the case n = 6.) If we express 
each of these portions of area parametrically and combine 
the expressions into a single integral, we find that the area 
bounded by the curve is given by the expression 



— yxdt, 



which as before has the same sign as the sense in which the 
boundary curve is traversed. 

Our formula even gives us the area, in a certain sense, in the case where 
the curve intersects itself. But we shall not enter into such a discussion 
here; the reader may if he wishes turn to § 2 of the appendix to this chapter 
(p. 311). 



V] THEORY OF PLANE CURVES 273 

We can express our formula for the area in a more elegant 
symmetrical form if we first transform the integral by integration 
by parts: 

/ yxdt= — xydt+xy 
Jt, Jt, 

Since the curve is closed, 

x(t ) = x(t 1 ), y(t ) = «/&), 



and therefore * 



A — — I yxdt = I xydt. 
Jt, Jt, 



If we form the arithmetic mean of the two expressions we obtain 
the symmetrical form 

1 f* 1 

A = — - (yx — xy)dt. 

3. Remarks and an Example. 

In connexion with these expressions we must make a remark 
of a fundamental nature. Both the proof and the statement 
of the formulae depend on a particular system of rectangular 
co-ordinates. But the value of the area, a purely geometrical 
quantity, cannot depend on the particular co-ordinate system 
chosen. It is therefore important to show that our integrals are 
unaltered in value by a change of co-ordinates. 

If the axes are merely displaced without rotation the integrals 
are clearly unaltered (see the footnote on p. 271). Let us then 
suppose that the axes are rotated through an angle a; instead 
of x and y we now have new variables £ and 17, denned by the 
equations x = $ cos a — 17 sin a, y = g sin a + i) cos a, the new 
variables being also functions of the parameter t. If we recall 
that x — £ cos a — r\ sin a and y = £ sin a + i] cos a, a short 
calculation gives us yx — xy = ij£ — &, so that 

A = ~ I /"V - ay)* = - 5 Phi ~ ft)*- 

* Instead of finding the second expression for the area by integration by 
parts, we could have derived it by using the fact that as regards the definition 
of area the K-axis and the y-axis are interchangeable, except that the sense 
of rotation which brings the a;-axis into the y-axis in the shortest way is 
opposite to the sense -which brings the j/-axis into the a-axis in the shortest 
way. 

10 (B798) 



*74 APPLICATIONS [Chap. 

This equation expresses the fact that the area is independent 
of the co-ordinate system. 

Our integral expression for the area is also independent of 
the choice of parameter. For suppose that we introduce a new 
parameter r by the equation t = r(t); we have 

dx dx dr dy _ dy dr 

dt dr dt' dt dr dt' 
so that 

-jC(»5-s)*-r('s-s)s* 

where t and r x are the initial and final values of the new 
parameter, corresponding to the parametric values t and ^ 
respectively.* 

As an example of the application of our formula for the area we con- 
sider the ellipse y = -V(o a — a: a ). In order to find its area we take 
a 

the tipper and lower halves of the ellipse separately and in this way 
express the area by the integral 

6 r +a 



b r +a , 
2 - / V(a*-x?)dx. 
a J - a 



If, however, we use the parametric representation x= acoet, y = b sin<, 
we find immediately that the area is given by the expression 



i-2ir 

ah I sin 2 1 dt. 



■f 

This can be integrated as on p. 216; it has the value dbit. 

* In this section we have based the definition of the area on the concept of 
integral and have shown that this analytical definition has a truly geometrical 
character, since it yields a quantity independent of the co-ordinate system. 
It is, however, easy to give a direct geometrical definition of the area bounded 
by a closed curve which does not intersect itself, as follows: the area is the 
upper bound of the areas of all polygons lying interior to the curve. The proof 
that the two definitions are equivalent is quite simple, but will not be given 
here. 



V] THEORY OF PLANE CURVES *75 

4. Areas in Polar Co-ordinates. 

For many purposes it is important to be able to calculate 
areas using polar co-ordinates. Let r =f(0) be the equation of 
a curve in polar co-ordinates. Let A{0) be the area of the region 
which is bounded by the x-axis (that is, the line 8 = 0), the line 
through the origin making an angle 8 with the z-axis, and the 
portion of the curve between 
these two lines. Then 

A\8) = \r\ 

For if we consider the radius 
vector corresponding to the 
angle 6 and that correspond- 
ing to the angle 8 + A0, and 
denote the smallest radius 
vector in this angular interval 
(cf. fig. 10) by r and the greatest by r l5 the sector lying 
between the radius vector 8 and the radius vector 8 + A0 
will have an area AA which lies between the bounds £r o 2 A0 
and \r^A8. Consequently 

1 r 2<A4 1 , 
2 ° -A0-2 ri ' 

and on passing to the limit as A8 -*■ 0, we obtain the relation 
given above. By the fundamental theorem of the integral cal- 
culus, the area of the sector between the polar angles a and /? 
is then given by the expression 

1 rP 

2 I 




0< 

Fig. io. — Element of area in polar co-ordinates 



. r*d8. 
2. 



If /? > a, this expression cannot be less than zero. Since we 
readily see that as 8 increases the point with co-ordinates (r, 8) 
describes the boundary of the region in the positive sense, this 
is in agreement with our previous convention for sign. 

As an example, let us consider the area bounded by one loop of a lemnia- 
cate. The equation of the lemniacate (of. p. 73) is r % = 2a a cos26, and 

we obtain one loop by letting 6 vary from — - to +-. This gives us the 
expression 



J-tH 



cob 20 (ft 



276 APPLICATIONS [Chap. 

for the area. This can be integrated at once by introducing the new vari- 
able u = 29; we find the value of the integral to be a 2 . 

5. Length of a Curve. 

Another important geometrical concept associated with a 
curve leads to an integration. This is the length of arc. 

We shall first explain geometrically how we are led to a 
definition of the length of an arbitrary curve. The elementary 
process of measuring a length consists of comparing the length 
to be measured with rectilinear standards of length. The sim- 
plest method is to apply our standard length to the curve, with 
its ends on the curve, and count the number of times that we 
have to repeat the process in order to pass from the beginning to 
the end of the curve; we can refine the method as required by 
using smaller and smaller standards of length. By analogy with 
this elementary intuitive idea, we set up the definition of the 
length of a curve in the following manner. We suppose that our 
curve is given by the equations a; = x(t), y = y(t), a^ti== ft. 
(This includes curves in the form y =f(x), since these can be 
written y=f(t), x= t.) In the interval between a and fi we 
choose points t = a, ^, t 2 , . . . ,t„= j8, in that order. The points 
on the curve corresponding to these values t„ we join in order by 
line segments, thus obtaining part of a polygon inscribed in the 
curve; we now measure the perimeter of this polygon. This 
length will depend on the way in which the points t v , or, as we 
may also say, the vertices of the polygon, are chosen. We now 
let the number of the points t v increase beyond all bounds, in 
such a way that the length of the longest sub-interval in the 
interval a ^ t 5S ft at the same time tends to 0; this makes the 
number of sides of our polygon increase without limit, while the 
length of the longest side tends to 0. The length of the curve 
is then denned to be the limit of the perimeters of these inscribed 
polygons, provided that such a limit does exist and is independent 
of the particular way in which the polygons are chosen. It is 
only when this assumption that the limit exists (assumption of 
rectifiability) is fulfilled that we can speak of the length of the 
curve. We shall soon see that very wide classes of curves can be 
proved to be rectifiable. 

To express the length analytically by an integral, in fact, we 
think of the curve as represented in the first instance by a function 



V] 



THEORY OF PLANE CURVES 



277 



y = f(x) with, a continuous derivative y 1 . By the points a = a^, 
x 2 , . . . , x n = 6 we divide up the interval a 5j x ^ 6 of the 
x-axis, over which our curve lies, into (n — 1) sub-intervals of 
lengths Aa^, . . . , ^x„- v In the curve we inscribe a polygon 
whose vertices lie vertically above these points. The total length 
of this inscribed polygon is given according to Pythagoras' 
theorem (cf. fig. 11) by the expression 

'Ay; 
kAa;,, 






: u^(m 



Ax„. 



But by the mean value theorem of the differential calculus the 
difference quotient Ay y /Ax v is equal to /'(£,), where g y is an 




Fig. zx. — Rectification of curves 



intermediate value in the interval Ax„. If we now let n increase 
beyond all bounds and at the same time let the length of the 
longest sub-interval Aa;„ tend to zero, then by the definition of 
integral our expression will tend to the limit 

Since this passage to the limit always leads us to the same result, 
namely, the integral, no matter how the subdivision of the interval 
is made, we have established the following theorem: 

Every curve y = f (x) for which the derivative f'(x) is con- 
tinuous is a rectifiable curve, and its length between x = a and 
x = b (b Sg a) is given by the formula 

s(o,6) = /V(l + y' 2 )^. 



a7» APPLICATIONS [Chap. 

If by s we denote tie length of arc measured from an arbitrary 
fixed point to the point with abscissa x, the above equation 
gives us the following expression for the derivative of the length 
of arc with respect to x: 

g-Vfl + rt 

Our expression for the length of arc is still subject to the 
special and artificial assumption that the curve consists of one 
single-valued branch above the x-axis. Parametric represen- 
tation frees us from this restriction. If a curve of the kind which 
we have been considering is given in parametric form by the 
equations x = x(t), y — y(t), then by introducing the parameter 
t in the above expression we obtain the parametric form of the 
length of arc 

,(«,/?) =/"V(* 2 +y 2 )<&, 

•'a 

where a and /S are the values of t which correspond respectively 
to the points of the curve x = a and x = b. 

This parametric expression for the length of a curve has a 
considerable advantage over the previous form in that it is not 
restricted to single-valued branches of curves, represented by 
the equation y —f(x), but instead holds for any arbitrary arcs 
of curves, including closed curves, provided that the derivatives 
x and y are continuous along the arcs. 

We recognize this most easily if we go back again to the 
formula for the length of the inscribed polygon. We suppose 
that along the arc x and y are continuous. As in the definition, 
we subdivide the interval a^-t^ft by points t = a, 
<!,..., t n = /?, with the differences At v and use the corresponding 
points on the curve as vertices of an inscribed polygon; in the 
passage to the limit w-><» we assume that the greatest difference 
Ai„ tends to 0. If we now write the length of the polygon in the 
form 

.!/'--'+«=5,V{(©'+(t)>- 

we see at once that this sum tends to the integral / \/(x 2 -\- y 2 ) dt; 
we need only recall the generalized method of formation of an 



V] THEORY OF PLANE CURVES 



279 



integral (cf. p. 133). If the curve is composed of several arcs of 
this type, which may join one another at corners, the expression 
for the length of the curve is simply the sum of the corresponding 
integrals. Collecting the results, we have the following statement: 
If in the interval a 5S t ^ /? the functions x(t) and y(t) are 
continuous and their derivatives ±(t), y(t) are also continuous, 
except perhaps for a finite number of jump discontinuities, the 
arc of x = x (t), y = y (t) has a length given by the expression 



f 



V(* 2 + f)dl, 



where this integral, if necessary, is to be taken as an improper 
integral in the sense of Chap. IV (p. 245). In virtue of this for- 
mula, in which a must be less than ft, there is a meaning in 
ascribing a negative length, given by the same formula, to an 
arc of a curve traversed in the direction in which the value of the 
parameter t decreases. The sign of the length of arc therefore 
depends on the choice of the parameter. If we introduce a new 
parametric expression for the same curve which does not re- 
verse the sense of description, that is, if we introduce a new para- 
meter by the equation r = r(t), where dr/dt > 0, we see a priori 
that our integral formula should give the same value no matter 
whether t or t is used as parameter; for the two integrals give 
the length of the same curve and must therefore be equal. This, 
however, may also be verified directly, for 

We now give the expression for the length of arc when the 
curve is expressed in polar co-ordinates. In the last expression 
we have only to substitute for * and y their values as given in 
formula (a) on p. 265 in order to obtain 

& + f = f 2 + rW, 
whence 

»(a,j8) = fy/{r*+rW)dt. 



280 APPLICATIONS [Chap. 

If we now change over from the parametric expression to the 
equation in the form r=/(0), by introducing as parameter 
t = 8 itself, so that 6 = 1, we have the expression 






for the length of arc. 



A simple example of the explicit calculation of the length of an arc is 

given by the parabola y = - x 2 ; for its length of arc we immediately obtain 

r b 2 

the integral / V(l + x 2 )dx, which with the substitution x = sinhtt 
becomes a 

Xar sinh b \ par sinh b ] 

cosh a wefot=- / (l + cosh2tt)cfot=- (tt + sinhu coshu) 
_ * sinh a " ^ar sinh a ^ 



ar sinho 
arsinha 



so that the length of arc of the parabola between the abscissae x= a and 
x = 6 is given by the expression 

«(o, 6) = - {ar sinh6 + b V(l + 6 a ) — ar sinho — aV(l + a 2 )}. 
For the catenary y = cosh a; we find that 

/*b pb 

a(a,b)= I V(l + ainh i x)dx~ I coshiia;, or s (a, 5)= sinh 6 — sinho. 

Finally, let it be noted that in many cases it is convenient 
to introduce as parameter the length of arc reckoned from some 
fixed point P on the curve, that is, to take x= x(s) and 
y=y(s). Points of the curve on opposite sides of P will cor- 
respond to values of s with opposite signs. In this case we have 



x z + f 



-<*}'-'• 



whence by differentiation 

xx + yy = 0; 
these two relations find frequent application. 

6. Curvature of a Curve. 

The area and the length of arc of a curve depend on the 
complete course of the curve. We now insert a discus- 
sion of a concept which has reference only to the behaviour of 
a curve in the neighbourhood of a point, namely, the curvature. 



V] THEORY OF PLANE CURVES 281 

If we think of the curve as described uniformly in the posi- 
tive sense, in such a way that equal lengths of arc are passed 
over in equal periods of time, the direction of the curve will 
vary at a definite rate, which we take as a measure of the curva- 
ture of the curve. If, therefore, we denote the angle between 
the positive direction of the tangent (p. 264) and the positive 
.c-axis by a, and if we think of a as a function of the length of 
arc s, we shall define the curvature k at the point corresponding 
to the length of arc s by the equation k = da/ds. We know that 
a = arc tan y', and hence by the chain rule 

da da . ds y" 1 

ds~ dx~dx~ l + y' z ' V(l + y' 2 ) 

(where the positive sign of the square root means that increasing 
values of x correspond to increasing values of s). The curvature 
is consequently given by the expression 



(l + y' 2 ) s ' r 

Using the parametric formulae for y 1 and y" we obtain the 
following simple expression for the curvature of a curve repre- 
sented parametrically: 

, x y — yx 

which, of course, can also be found directly from the equation 

a = arc tan - = arc cot -. 
x y 

In contrast with the previous expression, which is dependent on 
the equation y=f(x) and consequently involves a special 
assumption about the position of the arc with respect to the 
£-axis, the parametric expression for the curvature holds for all 
arcs along which x, y, x, and y are continuous functions of t and 
£ 2 + y 2 4= 0. In particular, it holds for points where x = 0, 
i.e. where dyjdx becomes infinite. 

If we introduce the length of arc s as parameter and recall 
that x 2 + y 2 = 1 and xx -f- yy = 0, we have 

k = xij — yx = y (x + y \ \ = y - = —%. 

10* (1788) 



382 APPLICATIONS [Chap 

We thus obtain a particularly simple expression for the curva- 
ture. 

The sign of the curvature is changed if we reverse the sense 
of description of the curve, that is, if we replace the parameter 
t or s by the new parameter t = — £ or <r = — s. For then x 
and y change sign, but not x, y, x 2 or y 2 , as the following simple 
calculation shows: 

£.{,„}-**_«,_« 

*.{.<„>-£[-«{.(„}]— §*-H,<-» 

(A similar calculation can be made for y.) In the case of the 

v" 
expression k = ■■ ■ ? first found, this fact is concealed, 

since it is natural and customary to think of the curve as de- 
scribed from left to right, in which case the square root can only 
be positive. 

As an example we consider the curvature of a positively de- 
scribed circle with radius a. If we start from the parametric 
representation a; = a cost, y — a&m.t, we immediately obtain 

k = l 
a 

The curvature of a positively described circle is therefore the re- 
ciprocal of its radius. This result assures us that our definition 
of curvature is really a suitable one; for in the case of a circle 
we naturally think of the reciprocal of the radius as a measure 
of the curvature. 

Let us put />= -. The quantity | p | == ,— -, is generally called 
k \h\ 

the radius of curvature of the curve at the point in question. 
For a given point on the curve, that circle which touches 
the curve at the point and there has the same sense of descrip- 
tion and the same curvature as the curve, and, more- 
over, has its centre on the positive or negative side of the normal 
according as h is positive or negative, is called the circle of curva- 
ture corresponding to the point. Let us think of the equation 
of the circle (or an arc of the circle containing the point in ques- 



V] THEORY OF PLANE CURVES 283 

tion) as written in the form y — g(x). Then at the point in ques- 
tion we have not only f(x) = g(x) and f'(x) = g'(x), as follows 
from the fact that the circle and curve touch, but in virtue of 
the relation 

f"(x) _, g" (x) 

V{1+/'W 2 } 3 V{l + 0» 2 } 3 

we also have 

f"(x) = g"(x). 

The centre of the circle of curvature is called the centre of 
cwrvatwre corresponding to the given point. Its co-ordinates 
are expressed parametrically by 



To prove this we need only make use of the formulae for the 
direction cosines of the normal, on which the centre of curvature 
lies at a distance 1/| h\ = | p\ from the tangent. These for- 
mulae give us an expression for the centre of curvature in terms 
of the parameter t. As t describes its range the centre of curva- 
ture describes a curve, the so-called evolute of the given curve; 
and since, with x and y, we have to regard x, y, and p as known 
functions of t, the formulae above give parametric equations 
for this evolute. 

For special examples the reader may be referred to § 3 (p. 287 
et seq.) and to the appendix (p. 307 et seq.). 

7. Centre of Mass and Moment of a Curve. 

We now come to some applications which bring us into the 
realm of mechanics. We consider a system of n particles lying 
in a plane. Let m^, m 2 , . . . , m n be the masses of these particles, 
and let y v y 2 , . . . , y n be their respective ordinates. We 
then call 

n 

T = S m v y p = m 1 y 1 + m^y* + . . . + m n y n 

i- = 1 

the moment of the system of particles with respect to the x-axis. 
The expression 77 = TjM, where M denotes the total mass 
m 1 + m 2 + . . . + m„ of the system, gives us the height of the 
centre of mass of the system of particles above the as-axis. We 



284 APPLICATIONS [Chap. 

define the moment with respect to the y-axis and the abscissa of 
the centre of mass in a corresponding way. 

We shall now see that this idea can easily be extended to 
give us a definition of the moment of a curve along which a mass 
is uniformly distributed, and of the co-ordinates £ and 77 of the 
centre of mass of such a curve. Merely for the sake of brevity 
we assume that the density has a constant value, say /x, along 
the curve; any continuous distribution could equally well be 
discussed. 

To arrive at this extension we go back to the consideration 
of a system of a finite number of particles and then pass to the 
limit. For this purpose we suppose that the length of arc s is 
introduced as a parameter on the curve, and that the curve is 
subdivided by (w — 1) points of division into arcs of lengths 
As x , As 2 , . . . , As n . The mass pAs { of each arc As< we represent 
as concentrated at an arbitrary point of the arc, say that with 
the ordinate y t . 

By definition the moment of this system of particles with 
respect to the x-axis has the value 

T = pXytAst. 

If now the greatest of the quantities As t tends to 0, this sum 
tends to a definite limit given by the expression 

T = ^f'yds = ix f'yVO- + V' 2 ) dx, 

which we shall therefore naturally accept as the definition of 
the moment of the curve with respect to the a-axis. Since the 
total mass of the curve is equal to its length multiplied by ju. 

: M («i — s ), 



pi 1 



we are immediately led to the following expressions for the co- 
ordinates of the centre of mass of the curve: 

/ yds I xds 

» *• t '• 
V= > S= • 

These statements are actually definitions of the moment and 
centre of mass of a curve; but they are such straightforward 



V) THEORY OF PLANE CURVES 285 

extensions of the simpler case of a number of particles that we 
naturally expect that — as is actually the case — any statement 
in mechanics which involves the centre of mass or the moment 
of a system of particles will be valid for curves also. In 
particular, the position of the centre of mass with respect to 
the curve is independent of the system of co-ordinates. 

8. Area and Volume of a Surface of Revolution. 

If we rotate the curve y =f(x), for which f(x) ^ 0, about 
the x-axis, it describes a so-called surface of revolution. The area 
of this surface, whose abscissae we suppose to lie between 
the bounds x and a^ > x , can be obtained by a discussion 
analogous to the preceding. For if we replace the curve by an 
inscribed polygon, instead of the curved surface we shall have 
a figure composed of a number of thin truncated cones. Fol- 
lowing the suggestions of intuition, we define the area of the 
surface of revolution as the limit of the areas of these conical 
surfaces when the length of the longest side of the inscribed polygon 
tends to zero. We know from elementary geometry that the 
area of each truncated cone is equal to its slant height multiplied 
by the circumference of the circular section of mean radius. 
If we add these expressions and then carry out the passage to 
the limit, we obtain the expression 

A = 2t7 rVV(! + V' 2 ) dx = 2tt Py ds 

J x, Ji a 

for the area. Expressed in words, this result states that the area 
of a surface of revolution is equal to the length of the curve 
generating it multiplied by the distance traversed by the centre 
of mass (Guldin's rule). 

In the same way we find that the volume interior to the 
surface of revolution and bounded at the ends by the planes 
x = x and x = a^ > x is given by the expression 



V = 77 / y 2 dx. 



This formula is obtained by following the suggestion of intuition 
that the volume in question is the limit of the volumes of 
the above-mentioned figures consisting of truncated cones. The 
rest of the proof is left to the reader. 



z86 APPLICATIONS [Chap. 

9. Moment of Inertia. 

In the study of rotatory motion in mechanics an important 
part is played by certain quantities called moments of inertia. 
These expressions will be briefly mentioned here. 

We suppose that a particle m at a distance y from the as-axis 
rotates uniformly about that axis with angular velocity ca (that 
is, in unit time it rotates through an angle co). The kinetic energy 
of the particle, expressed by half the product of the mass and 
the square of the velocity, is obviously 

We call the coefficient of Jco 2 , that is, the quantity my 1 , the 
moment of inertia of the particle about the x-axis. 

Similarly, if we have n particles with masses m^, m 2 , . . . , m„ 
and ordinates y v y 2 , . . . , y a we call the expression 

T^'Zm.y? 
■ 

the moment of inertia of the system of masses about the a;-axis. 
The moment of inertia is a quantity which belongs to the system 
of masses itself, without reference to its state of motion. Its 
importance lies in the fact that if the whole system is set in 
rigid rotation about an axis, without change of the distances 
between pairs of particles, the kinetic energy is obtained by multi- 
plying the moment of inertia about that axis by half the square 
of the angular velocity. Thus the moment of inertia about an 
axis plays the same part in rotation about an axis as is played 
by the mass in rectilinear motion. 

Suppose now that we have an arbitrary curve y =/(») lying 
between the abscissae x and x± (> x ), along which a mass is 
uniformly distributed with unit density. In order to define the 
moment of inertia of this curve we proceed just as we did in the 
sub-section 7 (p. 284); as before, we arrive at an expression 
for the moment of inertia about the :c-axis, namely, 

t x = /■>«*» = f W(i + y' 2 ) dx. 

For the moment of inertia about the y-axis we have the corre- 
sponding expression 

T v = fV ds = f 'zV(l + y'^dx 



V] THE CYCLOID 387 



3. Examples 

The theory of plane curves with its great variety of special 
forms and properties offers us a rich store of examples of 
these abstract concepts. But to avoid being lost in a mass of 
detail we must limit ourselves to a few typical applications. 

1. The Common Cycloid. 

From the equations (of. p. 261) x = a(t — sin*), y = ffl(l — cost), we 
at once obtain x = o(l — cos*), y = a sin*, whence the length of arc is 

«= f V(x* + y*)dt = /"V {2a 2 (1 — cost)}*. 
Jq Jo 

But since 1 — cost = 2 sin 2 - the integrand is equal to 2a sin-, and hence 
for ^ a g 2tu 2 2 

X a t t a / a\ a 

sin- dt = —4a cos - = 4a 11 — cos - 1 = 8a sin*-. 
2 2 2 4 

If, in particular, we consider the length of arc between two successive 
cuspa we must put a = 2tc, since the interval ^ t ^ 2jt of values of the 
parameter corresponds to one revolution of the rolling circle. We thus 
obtain the value 8a; that is, the length of arc of the cycloid between suc- 
cessive cusps is equal to four times the diameter of the rolling circle. 

Similarly, we calculate the area bounded by one arch of the oycloid 
and the x-axis: 

/ «= / yx dt = a 2 / (1 — cost) 2 * 

•'0 »0 

/.2ir 

= a 2 / (1 — 2 cost + cos 2 *) dt 
Jo 



«( ~ . < sin 2<\ 

= a 2 [t - 2 sin* + - + ——) 



2ir 

= 3a 2 *. 



This area is therefore three times the area of the rolling circle. 
For the radius of curvature p = 1/iwe have 



(*' + f) 3 2 = _2aV{2(l-cos*)}= -4a 
xy — yx 



. t 
sin- 

2 



at the points * = 0, t = ±27t, . . . this expression has the value zero. 
These are actually the cusps, where the cycloid meets the x-axis at right 
angles. 



288 APPLICATIONS [Chap. 

The area of the surface of revolution formed by rotating an arch of 
the cycloid about the x-axis is given according to our formula (p. 285) 

b y f8a /-2.T t 

A= 2n I yds = 2n / o(l — cost) . 2a sin - dt 
J J 2 

/.2ir f pit 

= 8o 2 7i/ sin 3 „ <ft = 16a a rc / sin 3 a aw 
J 2 J 

= 16a a 7t / (1 — cos a it) sinudu. 
Jo 

The last integral can be evaluated by means of the substitution cosm = v; 
we find that 

A = 16a a 7t( — cosm + - cos'm) = . 

3 lo 3 

As an exercise the reader may calculate for himself the height 7) of the 
centre of mass of the cycloid above the x-axis, and also the moment of 
inertia T x . The results are 

4 A a m 256 s 

•n == _ o = — and T m = — a 3 . 

1 3 2tm * 15 



2. The Catenary. 

The length of aro of the catenary has already been calculated as an 
example in the preceding section (p. 280), and we found its value to be 

» = / cosh x (fa = sink 6 — sinha. 

Ja 

For the area of the surface of revolution obtained by rotating the 
catenary about the x-axis, the so-called catenoid, we find 



6 1.1 j o /" 6 l + cosh2x 



A = 2tc f cosh a xax = 2n f 

Ja Ja 



dx 



= 7t(6 — a + sinh22> — - sinh2a). 
2 ^ 

From this we further obtain the height of the centre of mass of the aro 
from a to 6: 

m 6 — o + ~ sinh26 — - sinh2a 

tj = - — = _ __. 

Zns 2(sinh6 — sinha) 

Finally, for the curvature we have 

y" cosh a; 1 



fc = 



(1 _|_ y '2)3/2 C osh 3 a; cosh a x" 



V] THE ELLIPSE AND THE LEMNISCATE 289 

3. The Ellipse and the Lemniscate. 

The lengths of arc of these two ourves cannot be reduced to elementary 
functions, but belong to the class of " elliptic integrals " mentioned on 
p. 243. 

For the ellipse y = V (o a — x 8 ) we obtain 
a 

aJ V \ a? — 3? ) J V(l— £ 2 )(l-x 2 £>) 

where we have put x/a = %, 1 — 6 2 /a 2 = x 2 . By the substitution i; = sin <p 
this integral can be expressed in the form 

«= fV{a*— (a 3 — & 2 )sin 2 <p}(29 = a f V(l — x"sin 2 <p)d<p. 

Here, to obtain the semi-perimeter of the ellipse, we must let x traverse 
the interval from — a to +a, which corresponds to the interval 

— 1^5^+1 or — re/2 g <p ^ +7t/2. 

For the lemniscate, whose equation in polar co-ordinates is r 2 = 2a a cos 2t, 
we similarly obtain 

« = /V(r> + f*)dt = [Jfa oos2< + 2a 2 !^£f ) <ft 

■* •/ Tf \ COS .&{ / 

= aV2f J dt =aV2f- / * 

J V(cos2i) J V(l — 2 sin 2 <) 

If we introduce u = tan* as independent variable in the last integral, we 
have 

• i. «* j, du 

sin a ( = , at ■■ 



1 + u a ' 1 + u 1 ' 

and consequently 

,= aV2f , dw . 
J V(i — « 4 ) 

In a complete loop of the lemniscate u runs from — 1 to + 1. and the length 
of arc is therefore equal to 



a 



V2 



, r+ 1 du 
Li V(l - u 1 )' 



a special elliptic integral which played a great part in the researches of 
Gauss. 



«90 APPLICATIONS [Chap. 



Examples 

1. Calculate the area bounded by the semicubioal parabola y = **/*. 
the x-axis, and the lines x= a and x= b. 

2. Calculate the area of the region bounded by the line y = x and the 
lower half of the loop of the folium of Descartes. (Use the parametric 
representation found in Ex. 7, p. 267.) 

3. Calculate the area of a sector of the Archimedean spiral r = o9 
(a > 0). 

4. Calculate the area of the cardioid (Ex. 3, p. 267), using polar co- 
ordinates. 

5. Calculate the area of the astroid (Ex. 6, p. 267). 

6. Calculate the area of the pedal curve of the circle x* 4- y 2 = 1 with 
respect to a point P (x , 0) on the x-axis. Show that this area is least when 
P is at the origin. 

7. Do the same for the ellipse — + - = 1. 

a 2 6 2 

8. Find the parametric representation of the cardioid when the length 
of arc is used as parameter. 

9. Do the same for the cycloid. 

10. Calculate the length of aro of the semicubioal parabola y = a^' 2 . 

11. Calculate the length of the astroid. 

12. Calculate the length of arc of: 

(a) The Archimedean spiral r = a9 (a > 0). 
(6) The logarithmic spiral r = e m6 . 

(c) The cardioid (Ex. 3, p. 267). 

(d) The curve r=a(0 i — 1). 

13. Find the radius of curvature of (a) the parabola y = a; 2 ; (6) the 
ellipse x= a cos 9, y = b sin 9, as a function of x and of 9 respectively. 
Find the maxima and minima of the radius of curvature and the points 
at which these maxima and minima occur. 

14. Sketch the curve 

rf* ' fins 11. _ /•' s 



/" cos u , t sm u , 

x = I — = du, y = I — = du 

Jo Vu Jq Vu 



and determine its radius of curvature ( p). 

15. Show that the expression for the curvature of a curve x = x(t), 
y = y (t) is unaltered by rotation of axes and also by change of parameter 
given by t = 9(f), where 9'(t) > 0. 



V] THE ELLIPSE AND THE LEMNISCATE 291 

16. Let r = /(0) be the equation of a curve in polar co-ordinates. 
Prove that the curvature is given by the formula 



k — 


2r™ — rr" + r* 




(r* + r 


a\3/a ' 


r' = 


- d f r", 


dO 2 ' 



where 



17. Find the volume and surfaoe area of a zone of a sphere of radius r, 
i.e. of the portion of the sphere cut off by two parallel planes distant A a , ftj 
respectively from the oentre. 

18. Find the volume and surfaoe area of the torus or anchor ring obtained 
by rotating a circle about a line which does not intersect it. 

19. Find the area of the catenoid, the surface obtained by rotating an 
arc of the catenary y = coshx about the x-axis. 

20. Sketch the curve defined by the equations 

*= fcos(in^)dt, y«= / sin($7rf 2 )<tt. 
Jo Jo 

What is the behaviour of the curve as t runs from — 00 to +00T Cak 
culate the curvature k as a function of the length of arc. 

21. The curve for which the length of the tangent intercepted between 
the point of contact and the y-axis is always equal to 1 is called the tractrix. 
Find its equation. Show that the radius of curvature at each point of the 
curve is inversely proportional to the length of the normal intercepted 
between the point on the curve and the y-axis. Calculate the length of 
arc of the tractrix and find the parametric equations in terms of the length 
of arc. 

22. Let x — x(t), y = y(t) be a closed curve. A constant length p is 
measured off along the normal to the curve. The extremity of this seg- 
ment describes a curve which is called a parallel curve to the original curve. 
Find the area, the length of arc, and the radius of curvature of the parallel 
curve. 

23. Find the centre of mass of an arbitrary aro (o) of a circle of radius r, 
(6) of a catenary. 

24. Calculate the moment of inertia about the x-axis of the boundary 
of the rectangle a ^x f^b, a ^ y ^ p. 

25. Calculate the moment of inertia of an arc of the catenary y = coshx 
(a) about the x-axis, (6) about the y-axis. 

26. The equation y — f(x) + a, a £x ^ &, represents a family of 
curves, one for each value of the parameter a. Prove that in this family 
the curve with the least moment of inertia about the x-axis is that which 
has its centre of mass on the x-axis. 



z 9 2 APPLICATIONS [Chap. 

4. Some very Simple Problems in the Mechanics of a 

Particle 

Next to geometry the differential and integral caleulus are 
especially indebted to the science of mechanics for their early 
development. Mechanics rests upon certain basic principles 
which were first laid down by Newton; the statement of these 
principles involves the concept of the derivative, and their 
application requires the theory of integration. Without analysing 
these basic principles in detail, we shall illustrate by some 
simple examples how the integral and differential calculus are 
applied in mechanics. 

1. The Fundamental Hypotheses of Mechanics. 

Here we shall restrict ourselves to the consideration of a single 
particle, that is, of a point at which a mass m is imagined to be 
concentrated. We shall further assume that motion can only 
take place along a certain fixed curve, on which the position of 
the particle is specified by the length of arc s measured from a 
fixed point on the curve; in particular, the curve may be a straight 
line, in which case we use the abscissa x as the co-ordinate of the 
point instead of s. The motion of the point is determined by 
expressing the co-ordinate s= <f>(t) as a function of the time. 
By the velocity of motion we shall mean the derivative <f>'{t), 
or, as we shall also write, 



dt 



<f>'(t) = i. 



The second derivative, 



we call the acceleration. 

In mechanics we start from the assumption that the motion 
of a point can be explained by means of forces of definite direc- 
tion and magnitude. Newton's second fundamental law of 
mechanics may, in the case of motion on our given curve, be 
expressed as follows: 

The mass multiplied by the acceleration is equal to the force 
acting on the particle in the direction of the curve; in symbols 

ms = F. 



V] MECHANICS OF A PARTICLE 293 

Thus the direction of the force is always the same as that of the 
acceleration; its direction is that of increasing values of s if 
the velocity in that direction is increasing, otherwise it is opposed 
to the direction of increasing values of s. 

The law of Newton is in the first instance nothing more than 
a definition of the concept of force. The left-hand side of our 
equation is a quantity which can be determined by observation 
of the motion, by means of which we measure the force. But 
this equation has a far deeper meaning. As a matter of fact, it 
turns out that in many cases we can determine the acting force 
from other physical assumptions, without any consideration of 
the corresponding motion. The above 
fundamental law of Newton is then 
no longer a definition of force, but is 
instead a relation from which we can 
draw important conclusions about the 
motion. 

The most important example of a 
known force is given us by gravity. 
From direct measurements we know 
that the force of gravity acting on a 
mass m is directed vertically down- v * 

wards and is of magnitude mg, where "*£?££?££?- 
the constant g, the so-called gravita- 
tional acceleration, is approximately equal to 981 if the time 
is measured in seconds and the lengths in centimetres. If a 
mass moves along a given curve, we learn by experiment that the 
force of gravity in the direction of this curve is equal to mg cos a, 
where a denotes the angle between the vertical and the tangent 
to the curve at the point under consideration (cf. fig. 12). 

In the case of motion on our given curve the basic problem 
of mechanics is as follows: if we know the force acting on the 
particle (e.g. the force of gravity), we have to determine the 
position of the point, that is, its co-ordinate s or x, as a function 
of the time. 

If we restrict ourselves to the simplest case, in which this 
force * mf(s) is known at the outset as a function of the length 
of arc — so that the force is independent of the time — we shall 

* The separation of the factor m in the expression for the given force is not 
essential, but makes the formulae simpler. 




294 APPLICATIONS [Chap. 

show how the course of the motion along the curve can be found 
from the equation 

m 

Here we have to deal with a differential equation, that is, an 
equation from which an unknown function — here s(t) — is to be 
determined and in which the derivative of this function occurs 
as well as the function itself (cf. Chap. Ill, § 7, p. 178). 



2. Body Falling Freely. Resistance of the Air. 

In the case of the free fall of a particle along the vertical jr-axis. New- 
ton's law gives us the differential equation 

x=g. 

From this follows x(t) = gt + » , where v is a constant of integration. 
Its meaning is easily found by putting t = 0. We then find x(Q) = v ; 
that is, i> is the velocity of the particle at the instant from which the time 
is reckoned, the initial velocity. By another integration, we obtain 

x(t) = i£rf 2 + w « + No- 
where x is also a constant of integration, whose value is again found by 
putting t = 0; we thus find that x is the initial position, that is, the co- 
ordinate of the point at the beginning of the motion. 

Conversely, we can choose the initial position x and the initial velocity 
» arbitrarily, and then obtain the complete representation of the motion 
from the equation x = \gt* + v t + x . 

If we wish to take account of the effect of the friction or air resistance 
acting on the particle, we have to consider this as a force whose direction 
is opposite to the direction of motion and concerning which we must make 
definite physical assumptions.* We shall work out the results of different 
physical assumptions: (a) the resistance is proportional to the velocity, 
being given by an expression of the form — rx, where r is a positive con- 
stant; (6) the resistance is proportional to the square of the velocity, 
being of the form — rx 1 . In accordance with Newton's law we obtain for 
the equations of motion 

(a) mx= mg — r&, (6) mx = mg — rx*. 

If we at first consider x = u(t) as the function sought, we have x(l) — u(t), 

so that . . „, , 

(a) mu — mg — ru, (o) mu = mg — ru a . 

* These assumptions must be chosen to suit the particular system under 
consideration; for example, the law of resistance for low speeds is not the same 
as that for high (e.g. bullet velocities). 



V] MECHANICS OF A PARTICLE 295 

Instead of determining u as a function of t by these equations, we deter- 
mine t as a function of u, writing our differential equations in the form 

i„\ dt l ,m * 1 



dm, g — ru/m du g — ruf/m 

With the help of the methods given in the preceding chapter we can imme- 
diately carry out the integrations and obtain 

(o) t(u) - - ? log (l - -I u) + «„, 
r \ mg I 

(&)«(«)=- J*iog5LzJf + ^ 

where we have put V(m/rg) = k and where t„ is a constant of integration. 
Solving these equations for u, we have 



(6) «(<)= — gk 



mg f 

e -2 («-«,)/*_ 1 



(O) U(t) = - ^? (e-r(«-«.)/m _ 1)( 

r 



e -2(»-«.)/ft + !' 



These equations at once reveal an important property of the motion. 
The velocity does not increase with time beyond all bounds, but tends 
to a definite limit depending on the mass m. For 

(a) lim u(t) = ^?, (6) lim «(«) = J^i. 

A second integration, performed on our expressions for u(t) = x with the 
help of the methods of the preceding chapter, gives the results (which 
may be verified by differentiation) 

(a) x(t) = — ge-nt-t.)lm +^£4 + 0, 
r* r 

(6) x(t)=- log cosh J r l {t - < ) + c, 

where c is a new constant of integration. The two constants of integration 
t and c are readily determined if we know the initial position a(0) = x 
and the initial velocity x(0) = m(0) = »„ of the falling particle. 

3. The Simplest Type of Elastic Vibration. 

As a second example we consider the motion of a particle which moves 
along the jr-axis and is pulled back towards the origin by an elastic force. 
As regards the elastio force we assume that it is always directed towards 
the origin and that its magnitude is proportional to the distance from the 
origin. In other words, we take the force as equal to — tec, where the 
coefficient k is a measure of the stiffness of the elastic connexion. Since 



296 APPLICATIONS [Chap. 

k is assumed positive, the force is negative when x is positive and positive 
when x is negative. Newton's law now tells ua that 

mx = — kx. 

We cannot expect that this differential equation will determine the motion 
completely, but it is plausible to suppose that for a given instant of time, 
gay t = 0, we can arbitrarily assign the initial position a;(0) = x„ and the 
initial velocity x(0) = v ; that is, in physical language, that we can start 
off the particle from an arbitrary position with an arbitrary velocity and 
that thereafter the motion is determined by the differential equation. 
Mathematically this is expressed by the fact that the general solution of 
our differential equation contains two constants of integration, at first 
undetermined, whose values we find by means of the initial conditions. 
This fact we shall prove immediately. 

We can easily state such a solution directly. If we put to = V(k/m), 
we may at once verify by differentiation that our differential equation is 
satisfied by all the functions 

x(t) = Cj cosui + c 2 sincot, 

where e t and c 2 denote constants chosen arbitrarily. On p. 297 we shall see 
that there are no other solutions of our differential equation and hence 
that every such motion under the influence of an elastic force is given by 
the above expression. This expression can easily be put in the form 

x{t) = a sinco(i — 8) = — a sincoS cos cut + a coscoS sin cot; 

we need only write — a sincoS = c^ and a coscoS = Cj, thus introducing in- 
stead of Cj and c 2 the new constants a and 8. Motions of this type are said 
to be sinusoidal or simple harmonic. They are periodic; any state (i.e. 
position x(t) and velocity x(f)) is repeated after the time T = 2n/a, which 
is called the period, since the functions sincoi and coscoi have the period 
T. The number a is called the maximum displacement or amplitude of the 
oscillation. The number 1/T = co/27t is called the frequency of the 
oscillation; it measures the number of oscillations per unit time. We 
shall return to the theory of oscillations in Chap. XI (p. 501). 

4. Motion on a Given Curve. 

Finally, we shall discuss the most general form of the problem stated 
above, namely, the problem of motion along a given curve under an arbi- 
trary pre-assigned force mf(s). 

The point in question here is the determination of the function s(t) 
as a function of t by means of the differential equation 

■*• = /(*), 

where /(«) is a given function. This differential equation in s can be solved 
completely by the following device. 

We begin by considering any primitive function F(s) of /(«), so that 



V] MECHANICS OF A PARTICLE 297 

F '(a) = f(s), and multiply both sides of the equation * = /(«) = F'(a) 

by a. We can then write the left-hand side in the form — ( - a 2 J, as we see 

dt \& ' 

at onoe by differentiating the expression a 2 ; the right side F'{a)a, however, 

is the derivative of F(a) with respect to the time t, if in F{s) we regard the 

quantity £ as a function of t. Hence we immediately have 

dt \2 / dt l ' 
or by integration 

h* = F(s) + c, 

where c denotes a constant yet to be determined. 

da . 

Let us write this equation in the form -37 = V2(F(a) + c). We see that 

from this we cannot immediately find a as a function of t by integration. 
But we arrive at a solution of the problem if we at first content ourselves 
with finding the inverse function t(a), that is, the time taken by the particle 
to reach a definite position a. For this we have the equation 

dt 1 



/ 



da \>2{F(a) + 0} 

thus the derivative of the function t(a) is known, and we have 

da 
V2{F(a) + c} 

where o x is another constant of integration. As soon as we have performed 
this last integration we have solved the problem, for while we have not 
determined the position a as a function of t, we have inversely found the 
time t as a function of the position a. The fact that the two constants of 
integration c and c± are still available enables us to make the general 
solution fit special initial conditions. 

In the above example of elastic motion we have to identify x with a; 
we have f{a) = — to 2 s and correspondingly, say, F(a) = — $ to 2 * 2 . We 
therefore obtain 

*= 1 

da V(2c-o>V)' 



and further 



■-; 



da 



V(2c— &)V) 



This integral, however, can easily be evaluated by introducing o>«/V2c 
as a new variable; we thus obtain 

t = — arc sin — ^= + Cj, 
<a V2c 



298 APPLICATIONS [Chap. 

or, forming the inverse function, 

a = smco(< — Cj). 

CO 

We are thus led to exactly the same statement of the solution as before. 
From this example we also see what the constants of integration mean 
and how they are to be determined. If, for example, we require that at 
the time t = the particle shall be at the point a = and at that instant 
shall have the velocity «(0) = 1, we obtain the two equations 

■\/2c 

= sincoCj, 1 = V2c coscoc,, 

CO 

from which we find that the constants have the values Cj = 0, c = J. 
The constants of integration and c^ can be determined in exactly the 
same way when the initial position « and the initial velocity « (at time 
t = 0) are prescribed arbitrarily. 

Examples 

1. A point A moves with constant velocity 1 on a circle with radius r 
and centre the origin. The point A is connected to a point B by a line of 
constant length l(>r); B is constrained to move on the x-axis (cf. the 
orank, connecting-rod, and piston of a steam engine). Calculate the velocity 
and acceleration of B as functions of the time. 

2. A particle starts from the origin with velocity 4, and under the 
influence of gravity slides down a straight wire until it reaches the 
vertical line x = 2. What must the slope of the path be in order that 
the point may reach the vertical line in the shortest time? 

3. A particle moves in a straight line subject to a resistance producing 
the retardation ku\ where u is the velocity and k a constant. Find ex- 
pressions for the velocity (w) and the time (<) in terms of a, the distance 
from the initial position, and v , the initial velocity. 

4. A particle of unit mass moves along the x-axis and is acted upon 
by a force f(x) = — sinx. 

(a) Determine the motion of the point if at time t = it is at the 
point x = and has velocity v = 2. Show that as t -*■ 00 the particle 
approaches a limiting position, and find this limiting position. 

(6) If the conditions are the same, except that v may have any value, 
show that if v B > 2 the point moves to an infinite distance as t ->■ 00, 
and that if v < 2 the point oscillates about the origin. 

5. Choose axes with their origin at the centre of the earth, whose radius 
we shall denote by R. According to Newton's law of gravitation, a partiole 
of unit mass lying on the y-axis is attracted by the earth with a force 

— =— jpt where jx is the "gravitational constant" and M is the mass of 

the earth. 



V] 



MECHANICS OF A PARTICLE 



299 



(a) Calculate the motion of the partiole after it is released at the point 
y (> B); that is, if at time t = it is at the point y=y a and has the 
velocity v = 0. 

(b) Find the velocity with which the particle in (a) strikes the earth. 

(c) Using the result of (6), calculate the velocity of a particle falling 
to the earth from infinity, f 

6.* A particle of mass m moves along the ellipse r = k/(l — e cos 0). 
The force on the particle is cm/r 2 directed towards the origin. Describe 
the motion of the particle, find its period, and show that the radius vector 
to the particle sweeps out equal areas in equal times. 



5. Further Applications: Particle sliding down a Curve 

1. General Remarks. 

The case of a particle sliding along a frictionless curve under the in- 
fluence of gravity can be treated very simply by the method just described. 
We shall first discuss this motion 
in general, and then with special ¥1. 

reference to the cases of the 
ordinary pendulum and the oy- 
cloidal pendulum. We ohoose 
axes in such a way that the j/-axis 
points vertically upwards, that is, 
opposite to the direction of the 
force of gravity, and consider 
the curve as given in terms 
of a parameter 8 by the para- 
metric equations x = 9(6) = a;(0), 
y = (^(9) = y(0). A portion of 
the curve, for which the motion 
will be studied, is shown in fig. 13. 
At every point of the curve the force of gravity acts downwards (that is, 
in the direction of decreasing y) on the particle with magnitude mg. If we 
denote the angle between the negative y-axis and the tangent to the curve 
by a, according to the hypothesis stated on p. 293 the force acting along 
the direotion of the curve is 








Fig. 13 



mg cosa = —mg —. " , 



where 



dip 



■ _ &ty _ 



'-I-«w. '= I = +'«»• 



(Note that here the dash denotes the derivative with respeot to 6, and 
not with respect to as.) If in particular we introduce the length of arc a 

t This is the same as the least velocity with which a projectile would have 
to be fired in order that it should leave the earth and never return. 



300 APPLICATIONS [Chap. 

as parameter in place of 6, we obtain the expression — mg-E for the force 

ds 

along the curve. By Newton's law, therefore, the function s{t) satisfies 

the differential equation 

dy 

ds 

The right-hand side of this equation is a known function of s, since we 
know the curve and must therefore regard the quantities x and y as known 
functions of s. 

As in the last section, we multiply both sides of this equation by i. The 

left-hand side then becomes the derivative of - s a with respect to t. If in 

the function y(s) we regard s as a function of t, the right-hand side of our 
equation is the derivative of — gy with respect to t. On integrating, we 
therefore have 

where c is a constant of integration. In order to fix the meaning of this 
constant, we suppose that at the time t = our particle is at the point 
of the curve for which the value of the parameter is 6 and the co- 
ordinates are x = <p(0 o ), y = <l>{%), and that at this instant its velocity 
is zero, that is, «(0) = 0. Then putting t = we immediately have 
— 9Va + c = 0, so that 

-i' = -p(y-y„). 

Now instead of regarding s as a function of t we shall consider the inverse 
function t{s). For this we at once obtain 

dt_ = 1 

ds V{2g(y ll -y)}' 

which is equivalent to 

/• ds 

"' J V{2g(y -y)}' 

where c^ is a new constant of integration. As regards the sign of the square 
root, which is the same as the sign of i, we notice that if the particle moves 
along an arc which is lower than y e everywhere except at the ends, the 
sign cannot change. For the sign of s can change only where i = 0, that 
is, where y — y = 0. The integrand on the right is known in terms 
of the parameter 0, since the curve is known. Introducing G as inde- 
pendent variable, we obtain 

. fds dQ , T If ** + lf % \ ik 

1 " W A V { 2g { y -y )} " * ±H (i^)) ««' 

where the functions x" = <p'(0), y' = <1>'(Q), y = 4*(9) are known. In order 
to determine the constant of integration c, we note that for t = the 



V] 



PARTICLE SLIDING DOWN CURVE 



301 



value of the parameter must be 6 . This immediately gives us our solution 
in the form 







When integrated this equation represents the time taken by the particle 
to move from the parameter value 6 to the parameter value 6. The in- 
verse function 6(() of this function t(6) enables us to describe the motion 
completely; for at each instant t we can determine the point x = 9{6(t)}, 
y = <|>{6(f)} which the particle is then passing. 

2. Discussion of the Motion. 

From the equations just found, without an explicit expression for the 
result of the integration we can deduce the general nature of the motion 
by simple intuitive reasoning. 
We suppose that our curve is If •< 
of the type shown in fig. 14, 
that is, that it consists of 
an arc convex downwards; we 
take « as increasing from left 
to right. If we initially re- 
lease the particle at the point 
A with co-ordinates x = x , 
y=y<n corresponding to 6= 6 , 
the velocity increases, for the 
acceleration * is positive. The 
particle travels from A to the lowest point with ever-increasing velocity. 
After the lowest point is passed, however, the acceleration is negative, 

since the right-hand side —g-f-oi the equation of motion is negative. 

as 

The velocity therefore decreases. From the equation i* = — 2g(y — y ) we 

see at once that the velocity reaches the value when the particle reaches 

the point B whose height is the same as that of the initial position A. 

Since the acceleration is still negative, the motion of the particle must be 

reversed at this point, so that the particle will swing back to the point A; 

this action will repeat itself indefinitely. (The reader will recall that friction 

has been disregarded.) In this oscillatory motion the time which the point 

takes to return from B to A must clearly be the same as the time taken to 

move from A to B. If we denote the time required for a complete journey 

from A to B and back again by T, the motion will obviously be periodic with 

period T. If 6 and 4 are the values of the parameter corresponding to 

the points A and B respectively, the half-period is given by the expression 

2 V2g\Je V \Vo-y I I 



Fig. 14 



J_J f e > // y' a (9)+<]/s(6) \ I 

V2g\J eB VI <K9o)-<K9)/ r 



302 APPLICATIONS [Chap. 

If 6j is the value of the parameter corresponding to the lowest point of 
the curve, the time which the particle takes to fall from A to this lowest 
point is 



-jLI/*Jp^±*>| 



3. The Ordinary Pendulum. 

The simplest example is given by the so-called simple pendulum. 
Here the curve under consideration is a circle of radius 2: 

x = I sin 6, y — — I cos 6, 

where the angle 6 is measured in the positive sense from the position of 
rest. From the general expression above we at once obtain 

t = B. r dQ = F r rfe 

V g L a V (cosG - cos*) V? J_^ («in«! - sin^)' 

where a(0 < a < 7t) denotes the amplitude of oscillation of the pendulum, 
that is, the angular position from which the particle is released at time 
t = with velocity 0. By the substitution 

_ sin (6/2) du = cos ( 6/2) 
sin Ox/2)' 56 _ 2 sin (a/2) 

our expression for the period of oscillation of the pendulum becomes 

du 



r==2 I 1 r 1 

VyJ_,V(l-«»: 



)(1 — tt a sin 2 (a/2)) 

We have therefore expressed the period of oscillation of the pendulum 
by an elliptic integral. 

If we assume that the amplitude of the oscillation is small, so that 
we may with sufficient accuracy replace the second factor under the 
square root sign by 1, we obtain the expression 



2 a r 1 du 

NgJ^Vil-v?) 



as an approximation for the period of oscillation. We oan evaluate this 
last integral by formula 13 in our table of integrals (p. 206), and obtain 



the expression 2n ,. /- as an approximate value for T. 



'9 

I. The Cycloidal Pendulum. 

The fact that the period of oscillation of the ordinary pendulum is 
not strictly independent of the amplitude of oscillation caused Christian 
Huygens, in his prolonged efforts to construct accurate clocks, to seek 
for a curve such that the period of osoillation is strictly independent of 



V] 



PARTICLE SLIDING DOWN CURVE 



3°3 



the particular position on the curve at which the oscillating particle begins 
its motion.* Huygens recognized that the cycloid is such a curve. 

In order that a particle may actually be able to oscillate on a cycloid 
the cusps of the cycloid must point in the direction opposite to that of 
the force of gravity; that is, we must rotate the cycloid considered pre- 
viously (p. 261) about the s-axis (cf. fig. 15). We therefore write the equa- 
tions of the cycloid in the form 

x — as(6— sinO), 
y= o(l-f cos0), 

which also involves a translation of the curve through a distance 2a in 
the positive ^-direction. The time which the particle takes to travel from 
a point at the height 

y = a(l + cosa) (0<a<7t) 




Fig. 15. — Path described by a cycloidal pendulum 

down to the lowest point, by the formula worked out on p. 301, is 



We now use the equation 

00s a — cos9 = 2 1 cos 2 - ■ 
V 2 
this gives 



T _ la 



VH- cos 1) 






dO. 



We then work out the definite integral, making use of the substitution 



6 a. . 8 ,„ 

cos - = u cos - , sin — ao : 
2 2 2 



* The oscillations are then said to be isochronous. 



304 APPLICATIONS [Chap. 

This gives 



J 



. e 

sin 



dQ = — 2 / -j-^ = — 2 arc sinu, 



V( cos 1 _cos 1) 



V(l — u") 



and we therefore obtain 






COS - 

2 

are sin 

a 

eos- 

2 



-v£ 



The period of oscillation T, therefore, is actually independent of the ampli- 
tude a. 

6. Work 

1. General Remarks. 

The concept of work throws new light on the considerations of the last 
section and on many other questions of mechanics and physics. 

Let us again think of the particle as moving on a curve under the 
influence of a force acting along the curve, and let us suppose that its 
position is specified by the length of arc measured from any fixed initial 
point. The force itself will then, as a rule, be a function of s. We assume 
that it is a continuous function f(s) of the length of arc. This function 
will have positive values where the direction of the force is the same as 
the direction of increasing values of s, and negative values where the 
direction of the force is opposite to that of increasing values of a. 

If the magnitude of the force is constant along the path, by the worlt 
done by the force we mean the product of the force by the distance 
(«!—«„) traversed, where «j denotes the final point and s the initial point of 
the motion. If the force is not constant we define the work by means of 
a limiting process. We subdivide the interval from «„ to s 1 into n equal or 
unequal sub-intervals and notice that if the sub-intervals are small, the 
force in each one is nearly constant; if <r v is a point chosen arbitrarily in 
the v-th sub-interval, then throughout this sub-interval the force will 
be approximately /(c„). If the force throughout the v-th sub-interval were 
exactly /(a,,), the work done by our force would be exactly 

S/(a„)As,,, 
>•- 1 
where A«„ as usual denotes the length of the v-th sub-interval. If we now 
pass to the limit, letting n increase beyond all bounds while the length 
of the longest sub-interval tends to zero, then by the definition of an 
integral our sum will tend to 

W=f H f(8)da, 
which we naturally call the work done by the force. 



V] WORK 305 

If the direction of the force and that of the motion are the same, the 
work done by the force is positive; we then say that the force does work. 
On the other hand, if the direction of the force and that of the motion are 
opposed, the work done by the force is negative; we then say that work 
is done against the force* 

If we regard the co-ordinate of position « as a function of the time t, 
so that the force /(«) = p is also a function of t, then in a plane with rect- 
angular co-ordinates s and p we can plot the point with co-ordinates 
s = s(t), p = p(t) as a function of the time. This point will describe a 
curve, which may be called the work diagram of the motion. If we are 
dealing with a periodic motion, as in the case of any machine, then after 
a certain time T (one period) the moving point s(t), p(t) will return to the 
same point; that is, the work diagram will be a closed curve. In this case 
the curve may consist simply of one and the same arc, traversed first 
forwards and then backwards; this happens, for instance, in elastic 
oscillations. But it is also possible for the curve to be a more general 
closed curve, enclosing an area; this is the case e.g. with machines in 
which the pressure on a piston is not the same during the forward stroke 
as during the backward stroke. The work done in one cycle, that is, in 
time T, will then be given simply by the negative area of the work dia- 
gram, or in other words, by the integral 






l o+ T ... ds ,, 
p(t)~dt, 
at 



where the interval of time from t„ to t B + T represents exactly one period 
of the motion. If the boundary of the area is positively traversed the work 
done is negative, if negatively traversed the work done is positive. If 
the curve consists of several loops, some traversed positively and some 
traversed negatively, the work done is given by the sum of the areas of 
the loops, each with its sign changed. 

These considerations are illustrated in practice by the indicator diagram 
of a steam engine. By a suitably-designed mechanical device a pencil is 
made to move over a sheet of paper; the horizontal motion of the pencil 
relative to the paper is proportional to the distance s of the piston from 
its extreme position, while the vertical motion is proportional to the steam 
pressure, and hence proportional to the total force p of the steam on the 
piston. The piston therefore describes the work diagram for the engine 
on a known scale. The area of this diagram is measured (usually by means 
of a planimeter) and the work done by the steam on the piston is thus 
found. Here we also see that our convention for the sign of an area, as 
discussed in § 2, No. 1 of this chapter (p. 271), is not of exclusively 
theoretical interest. For it sometimes happens when an engine is running 
light, that the highly expanded steam at the end of the stroke has a pres- 

* Note that here we must carefully distinguish the force of which we are 
speaking. For example, in lifting a weight the work done by the force of gravity 
is negative: work is done against gravity. But from the point of view of the 
person doing the lifting the work done is positive, for the person must exert 
a force opposed to gravity. 

11 («798) 



3©6 APPLICATIONS [Chap. 

sure lower than that required to expel it on the return stroke; on the 
diagram this is shown by a positively traversed loop; the engine 
itself is drawing energy from the flywheel instead of furnishing energy. 

2. The Mutual Attraction of Two Masses. 

Let us suppose that a particle attracts another particle according to 
Newton's law of attraction; as a first example we shall consider the work 
done by the force of attraction as the second particle moves along the 
line joining the two particles. According to Newton's law of gravitation, 
the attracting force is inversely proportional to the square of the distance. 
If we imagine the first particle at rest at the origin and the second particle 
at the distance r from the origin, the attracting force is given by the 
expression 

where (i is a positive constant. The work done by this force when the 
particle moves from the distance r to the distance rj(<r) is therefore 
positive and equal to the integral 



rnds /l IN 



If, by means of an opposing force, the particle is moved farther away 
from the origin, going from the distance r to a distance r x > r, the work 
done by the force of attraction will, of course, still be given by this integral 
(now negative). The work done by the opposing force has the same numeri- 
cal value, but the opposite sign; it is therefore equal to ix ( - — -). If we 

\r rj 
think of the final position as being chosen farther and farther away, this 

approaches the limiting value ", which we may call the work which must 

r 

be done against the force of attraction in order to move the particle from 

the distance r to " infinity ". This important expression is called the 

mutual potential of the two particles. Here, therefore, the potential is 

denned as the work required to separate two attracting masses completely; 

for example, the work required in order to tear an electron completely 

away from an atom (ionization potential). 

3. The Stretching of a Spring. 

As a second example we consider the work done in stretching a spring. 
As is usual in the theory of elasticity, we assume (cf. p. 295 also) that the 
force needed to stretch the spring is proportional to x, the increase in the 
length of the spring, that is, p = lex, where k is a constant. The work 
which must be done in order to stretch the spring from the unstressed 
position x = to the final position x = x t is therefore given by the integral 







kx dx = £ kx t % . 



V] WORK 307 

4. The Charging of a Condenser. 

The concept of work in other branches of physios can be treated in a 
similar way. For example, we may consider the charging of a condenser. 
If we denote the quantity of electricity in the condenser by Q, its capacity 
by G, and the difference of potential (voltage) across the condenser by V, 
then we know from physics that Q = GV. Moreover, the work done in 
moving a charge Q through a difference of potential V is equal to QV. 
Since in the charging of the condenser the difference of potential V is not 
constant but increases with Q, we perform a passage to the .limit exactly 
analogous to that on p. 304 and as the expression for the work done in 
charging the condenser we obtain 

where Qj is the total quantity of electricity passed into the condenser and 
Fj is the difference of potential across the condenser at the end of the 
charging process. 



Appendix to Chapter V 

1. Properties of the Evolute 
The parametric equations 

^ x ~ p VW+f)' v==y+p VWW)' 

for the evolute of a given curve x = x(t), y = y{t) (cf . p. 283) 
enable us to deduce some interesting geometrical relations 
between it and the given curve. For convenience we use the 
length of arc s as parameter, so that 

x 2 + y z = 1 and xx + yy = 0, 

p x y 

or py = x and px = — y. 

We thus have i—x—py, tj = y+ px; 
on differentiation these give 

i = x— py— 'py=—py, y = y+ p*'+ p*= p&, 
and therefore £x + i# = 0. 



308 APPLICATIONS [Chap. 

Since the direction cosines of the normal to the curve are given 
by — y and x, it follows that the normal to the curve is tangent to 
the evolute at the centre of curvature; or, the tangents to the evolute 
are the normals of the given curve; or, the evolute is the " envelope " 
of the normals (cf. fig. 16). 

If further we denote the length of arc of the evolute, measured 
from an arbitrary fixed point, by a, we have 



©'-'- 



£ 2 + 



From the above formulae, since x 2 -f- y 2 = 1, we obtain 

so that if we choose the direction in which a is measured in a 
suitable way, 

6= p, 
provided that a 4= 0, 

or on integration 

°i — 0b = Pi — Po- 

That is, the length of arc of the evolute between two points is equal 
to the difference of the corresponding radii of curvature, provided 
that p remains different from zero for the arc under consideration. 

This last condition is not superfluous. For if p changes sign, 
then from the formula a = p we see that on passing the corre- 
sponding point of the evolute the length of arc a has a maximum 
or minimum; that is, on passing this point we do not simply 
continue to reckon a onward, but must reverse the sense in which 
a is measured. If we wish to avoid this, on passing such a point 
we must change the sign in the above formula, i.e. put a = — p. 

It may also be noted that the centres of curvature which 
correspond to maxima or minima of the radius of curvature are 
cusps of the evolute. (The proof will not be given here.) 

The geometrical relationship which we have just found can 
be expressed in yet another way. If we imagine a flexible inex- 
tensible thread laid along an arc of the evolute and stretched 
so that a part of it extends away from the curve tangentially to 
it, and if in addition the end-point Q of this thread lies on the 
original curve C, then as we unwind the thread the point Q will 
describe the curve C. This accounts for the name evolute 



V] PROPERTIES OF THE EVOLUTE 309 

(eoolvere, to unwind). The curve C is called an involute of the 
evolute E. On the other hand we may start with an arbitrary 
curve E and construct its involute C by this unwinding process. 
We then see that E conversely is the evolute of C. 

To prove this we consider the curve E, which is now the 
given curve, as given in the form £ = f (cr), V = V ( a )> where the 
current rectangular co-ordinates are denoted by £ and 77 and 
the parameter a is the length of arc. The winding is done as 
indicated in fig. 17; when the thread is completely wound on to 
the evolute E, its end Q coincides with the point A of E corre- 





Fig. 16. — Evolute (B) Fig. 17. — Involute (O 

sponding to the length of arc o. If the thread is now unwound 
until it is tangent to the evolute at the point P, corresponding 
to the length of arc a ^ a, the length of the segment PQ will be 
(a — a) and its direction cosines will be £ and t), where the dot 
denotes differentiation with respect to a. Thus for the co- 
ordinates x, y of the point Q we obtain the expressions 

x = £+ (a — ct)|, y = t\ + (o — a)i), 

which give the equations for the involute described by the point 
Q in terms of the parameter a. By differentiation with respect 
to a it follows that 

*=£-£+(«- *)£= («- °)l 
y = v — v + (° — aYv = (« — a )v- 



3io APPLICATIONS [Chap. 

And since £| + ijij = 0, we at once find that 

fz -f yy = 0, 

which shows that the line PQ is normal to the involute C. We 
can therefore state that the normals to the curve C are tangent 
to the curve E. But this is the characteristic property of E, the 
evolute of C. Hence every curve is the evolute of all its involutes. 




Fig. 18. — The cycloid as evolute and involute 



As a particular case we consider the evolute of the cycloid x = t — sin*, 
y-'l — cos*. By pp. 281, 283, 



% = x- 



. i a + y* 

y ...._ , 

xy — yx 



y + x 



* ** + 9\ 



xy— yx 



we therefore obtain the evolute in the form $ = < + sin*, yj = — 1 + cos*. 
If we put < = t + 7t, then 5 — jt = t — sinx and i) + 2 = 1 — cost, and 
these equations show that the evolute is itself a cycloid which is similar 
to the original curve, and can be obtained from it by 
translation, as indicated in fig. 18. 

As a further example we shall work out the equa- 
tion for the involute of the circle. We begin with the 
circle 5= cost, rj = sin* and unwind the tangent, as 
indicated in fig. 19. The involute of the circle is then 
given in the form 




x ■■ 



cos* + * sin*, y = — sin* + *cos*. 



„. lit Finally, we shall determine the evolute of the ellipse 

of the circle x = a cos*, y = 6 sin*. We at once have 



, . tf a + t a 2 

5 = x— $ — " — 



V 



xy — yx 



cos 8 * 



and 



1 = y + *- 



Jl = - 



o s -6 s 



sin 8 *, 



xy—yx b 

which is a parametric representation of the evolute. If from these equations 



V] 



PROPERTIES OF THE EVOLUTE 



3" 



we eliminate t in the usual way, we obtain the equation of the evolute in 
non-parametric form: 

(a£)2/8 + (6t)) 2/3 = (a 2 - 6 2 ) 2/s - 

This curve is called an astroid. Its graph is given in fig. 20. By means 
of the parametric equations we may readily convince ourselves that the 
centres of curvature corresponding to the vertices of the ellipse are actually 
the cusps of the astroid. 




Fig. ao. — Evolute of the ellipse 

Examples 

1. Show that the evolute of an epicycloid (Ex. 2, p. 267) is another 
epicycloid similar to the first, which can be obtained from the first by 
rotation and contraction. 

2. Show that the evolute of a hypocycloid (Ex. 4, p. 267) is another 
hypocycloid, which can be obtained from the first by rotation and ex- 
pansion. 



2. Abbas bounded by Closed Curves 

We saw in § 2 (p. 271) that the area bounded by a closed 
curve x = x (t), y—y (t), t ^ t ^ t^ which nowhere intersects 
itself (a so-called simple closed curve) is given by the integral 



-f'y{t)x(t)dt, 



where the value obtained is positive or negative according 
as the sense in which the boundary is described is positive or 



312 



APPLICATIONS 



[Chap. 



negative. We shall now extend this result to more general curves. 
Suppose that the curve C, given by the equation x=x(t), 
y=y (t), intersects itself in a finite number of points, thus divid- 
ing the plane into a finite number of portions R 1 , R 2 , .... Sup- 
pose further that the derivatives are continuous, except perhaps 
for a finite number of jump discontinuities, and that x 2 -j- y* =j= 0, 
except perhaps at a finite number of values of t which may 
correspond to corners. Finally, it is assumed that the curve 
has a finite number of lines of support (p. 270). 

To each region R { we then assign an index fi ( denned in the 
following way: we choose an arbitrary point Q in R iy not lying 
on any line of support, and erect the line extending from Q 



y\ 




-*-x 



Fig. 21 



upwards, in the direction of the positive y-axia. We count the 
number of times the curve C crosses the half-line from right to 
left, and subtract the number of times the curve C crosses from 
left to right; the difference is the index /*<. For example, the 
interior of the curve illustrated in fig. 6 (p. 269) has the 
index fi = +1; and in fig. 21 the regions R 1 , . . . , R & have the 
indices ju.j = — 1, [i 2 — +1> H-3 = +2> p-i = — 2, /x 5 = — 1. This 
number ^< actually does depend on the region R t and not on the 
particular point Q chosen in R ( , as we readily see in the following 
manner. We choose any other point Q' in R t , not on a line of 
support, and join Q to Q' by a broken line lying entirely in the 
region R { . As we proceed along this broken line from Q to Q' 
the number of right-to-left crossings minus the number of left- 
to-right crossings is constant; for between lines of support the 
number of crossings of either type is unchanged, while on 
crossing a line of support either the number of crossings of both 
types increases by one, or else both the numbers decrease by one; 
in either case, the difference is unaltered. In the case where the 



V] AREAS BOUNDED BY CLOSED CURVES 313 

line of support meets the curve at several different points, say 
A,B,...,H,we consider it as several different lines of support, 
FA, FB, . . . , FH, where F is the point of the a;-axis vertically 
below all the points A, B, ... , H. Our argument then applies 
to each of these lines. Hence the number //.< has the same value 
whether we use Q or Q' in determining it. 

In particular, if our curve does not intersect itself, the interior 
of the curve consists of a single region R whose index is +1 or 
— 1 according as the sense in which the boundary is described 
is positive or negative. To see this we draw any vertical line 
(not a line of support) intersecting the curve; on this line we 
find the highest point of intersection (P) with the curve, and in 
R we choose a point Q below P and so near it that no point of 
intersection lies between P and Q. Then above Q there lies one 
crossing of the curve, which if the curve is traversed positively 
must be a right-to-left crossing, so that /* = -{-1; otherwise 
fi = — 1. As we have just seen, this same value of p holds 
for every other point of R. For such a curve, and in fact for all 
closed curves, one of the regions, the " outside " of the curve, 
extends unboundedly in all directions; we see immediately that 
this region has index 0, and henceforth neglect it. 

Our theorem about the area is now as follows: the value of 

the integral — / yx dt is equal to the sum of the absolute areas of 
the regions R f , each area R ( being counted /x< times; in symbols 



— / yxdt = S/i 4 1 area R { |. 



The proof is simple. We assume, as we are entitled to do, 
that the whole of the curve lies above the x-axis (cf . footnote, 
p. 271). The lines of support cut R f into a finite number of por- 
tions; let r be one of these portions. Then on taking the integral 

— I yxdt for each single- valued branch of the curve, we find that 

the absolute area of r is counted +1 times for each right-to-left 
branch over r and — 1 times for each left-to-right branch over 
r, in all fj. f times. The same is true for every other portion of R ( ; 
hence R t is counted /*,< times. Thus the integral round the com- 
plete curve has the value S/ij | area R ( |, as stated. This for- 
mula agrees with what we have found for simple closed curves, 

11* (B798) 



3H APPLICATIONS [Chap. V 

as we recognize from the discussion of the values of ju. for such 
curves. 

The definition given for the index fj, t has the disadvantage 
of being stated in terms of a particular co-ordinate system. As 
a matter of fact, however, it can be shown that the value of fi t 
is independent of the co-ordinate system and depends solely on 
the curve; but we shall not prove this here. 



CHAPTER VI 

Taylor's Theorem and the Approximate 
Expression of Functions by Polynomials 

In many respects the rational functions are the simplest 
functions of analysis. They are formed by a finite number 
of applications of the rational operations of calculation, 
while in the last resort the formation of every other function 
involves a more or less concealed passage to the limit from 
rational functions. The questions whether and how a given func- 
tion can be expressed approximately by rational functions, in 
particular by polynomials, are therefore of great importance both 
in theory and in practice. 

1. The Logarithm and the Inverse Tangent 

1. The Logarithm. 

We begin by considering some special cases in which the 
integration of the geometrical progression leads almost at oncp 
to the desired approximations. We first remind the reader of 
the following fact. For q =)= 1 and for positive integers n, we 
have 

1 *,_.■_«, i _„-i . 



1-q 

where r„ = 



= 1 + q + f + . . . + J"" 1 + r„ 



If | q | < 1 the remainder r„ tends to as n increases, and we 
then obtain (pp. 34-35) the infinite geometric series 

1 4- a + a 2 + . . . with the sum , . 

31 1 — q 



316 TAYLOR'S THEOREM [Chap. 

As our starting-point we take the formula 

it 



lo g{ l + x)=f oT 



+ t 



and expand the integrand in accordance with the above formula, 
putting q = — t. Then by integration we at once obtain 

«.2 <r<3 ™i »n 

iog(i + *) = »- 1 + 1_ *+_... + (_ iri + b., 



where R n = fr„dt = (—1)" /" n - 



< n «ft 



Hence for any positive integer n we have expressed the 
function log(l + x) approximately by a polynomial of the n-th 
degree, namely, 

2 3 v ' n 

at the same time the quantity R„, the remainder, specifies the 
amount of the error made in this approximation. 

In order to estimate the accuracy of this approximation, 
we need only have an estimate for the remainder R n ; and such 
an estimate is given us immediately by the integral estimates 
on p. 126. If at first we suppose that x ^ 0, then in the whole 
interval of integration the integrand is nowhere negative and 
nowhere exceeds t n . Consequently 

1 •'0 M + 1 

and we therefore see that for every value of x in the interval 
^ x £J 1 this remainder can be made as small as we like by 
choosing n large enough (cf. p. 32). If, on the other hand, the 
quantity a; is in the interval — 1 < x £J 0, the integrand will 
not change sign and its absolute value will not exceed 1 1 | n /(l + x), 
and we thus obtain the estimate for the remainder 



l E -lSr^X"^-(TT^ 



n+l 



+ xJo (l + a! )( n+ l) 

We see, therefore, that here again the remainder is arbitrarily 
small when n is sufficiently large. Of course, our estimate has 
no meaning when we put x = — 1. 



V1J LOGARITHM AND INVERSE TANGENT 317 

Summing up, we can say that 

l0g{l + z)=X-^+^-+... + (-l)r>-l X - + R n , 

2 3 n 

where the remainder R n tends to zero as n increases, provided 
that x lies in the interval * — 1 < x j£ 1. From the above 
inequalities we can, in fact, find an estimate for the remainder, 
independent of x, which is valid for all values of a; in the interval 
— 1 + h ^ x ^ 1, where h is a number such that < h ^ 1. 
For then 

1 1 



l#„ 



'hn+l' 



and this formula shows us that in the whole interval the function 
log(l + a;) is expressed approximately by our polynomial of the 

n-th degree, the error being nowhere greater than . 

h n + 1 

We leave it to the reader to convince himself that for all values 

of x for which | x | > 1 the remainder not only fails to approach 

zero, but, in fact, increases numerically beyond all bounds as 

n increases, so that for such values of x our polynomial does not 

give us an approximation to the logarithm. 

The fact that in the above interval the remainder R n tends 

to zero may be expressed by saying that in this interval we have 

the infinite series f 

ffZ /y3 rf\ 

108(1+*)=*-!+!-!+-... 

for the logarithm. If in this series we insert the particular 
value x = 1, we obtain the remarkable formula 

log 2=1-1+---+— ... 
8 2^3 4 

This is one of the relations whose discovery made a deep 
impression on the minds of the first pioneers of the differential 
and integral calculus. 

* It is to be noted that this interval is open on the left and closed on the 
right. 

I Infinite series will be considered in detail in Chap. VIII (p. 366). 



318 TAYLOR'S THEOREM [Chap. 

The above approximation for the logarithm leads us to 
another formula which is useful for many purposes, particularly 
in numerical calculations. Provided that — 1 < x < 1, we have 
only to write — x in place of a; in the above formula to obtain 

sp2 /*t3 nA 

log(l- a3 )=- a! -|-|-|-..._S . 

Taking n as even and subtracting, we have 

1 , 1 + x , x 3 , x 5 . , x n ~ x , « 

Z 1 — x 3 5 w — 1 

where R„ is given by the expression 
.dt. 



~~ Jo 1 — 



On account of the relation 

n+ 1 1 — x 2 

the remainder tends to zero as n increases, a fact which we 
again express by writing the expansion as an infinite series: 

1, 1 + x . , . x 3 . x 5 . x 1 . 

- log = ar tanh x= x+ — + — [-—+..., 

2 5 1 — x ^3 5 7 

for all values of x such that \x\ < 1. 

An advantage of this formula is that as x traverses the in- 

1 -4- x 
terval from — 1 to 1, the expression ranges over all positive 

1 — x 

numbers. Hence if the value of x is suitably chosen this series 

enables us to calculate the value of the logarithm of any positive 

number, with an error not exceeding the above estimate for R n . 

2. The Inverse Tangent. 

We can treat the inverse tangent in a similar way if we 
begin with the formula, true for every positive integer n, 
1 



1 + t* 



1 — t 2 + t l — + . . . + (— l)n-lf2— 8 + Tn 



VI] LOGARITHM AND INVERSE TANGENT 319 

t 2n 
where r n = ( — 1)™ 



By integration, we obtain 

arc tana; = x— _ + _ + ...+ (— l)"" 1 + R n , 

3 5 In — 1 



Jrx fin 
ol + P 



and we see at once that in the interval — 1 ^ x ^ 1 the re- 
mainder R„ tends to zero as n increases, for by the mean value 
theorem of the integral calculus 



r\x\ I _ I 2n+l 

\R n \^f t 2n dt = LH 

1 " ' —Jo 2n 4- 1 



+ 

From the formula for the remainder we can also show fairly 
easily that for | x | > 1 the absolute value of the remainder 
increases beyond all bounds as n increases. We have accord- 
ingly deduced the infinite series 

arc tana; = x— - + — !-•••» 

3 5 

valid for I x I ^ 1. For x = 1, since arc tan 1 = - , we have 

4 

' 7 =1- 1 + -- + 

4 3 + 5 + '--' 

as remarkable a formula as that previously found for log 2. 



Examples 

1. Prove that x-% + f < log(l + x) < x- * + ** (x > 0). 
4 2 3(1 + a;) 2 3 



Hence find log- to 2 places. 



2. Calculate log - to 3 places, using the series 

5 

log(l + a;) = x — g + -—.... 

Prove that the result is accurate to 3 places. 

3. How many terms of the series for log(l + x) must be used in order 
to obtain log(l + x) to within 10 per cent if 30 ^ x ^ 31? 



320 TAYLOR'S THEOREM [Chap. 



2. Taylor's Theorem 

An approximate representation by rational functions, as in 
the special cases above, can also be obtained in the case of an 
arbitrary function /(a;), about which we assume only that for all 
values of the independent variable in an assigned closed interval 
the function possesses continuous derivatives up to the 
(n + l)-th order at least. In most of the cases which actually 
occur the existence and continuity of all the derivatives of the 
function is known to begin with, so that for n we can choose 
any arbitrary integer. 

The approximation formula which we shall now derive was 
discovered in the early days of the differential and integral cal- 
culus by Taylor, a student of Newton's, and is known as Taylor's 
theorem *. 

1. Taylor's Theorem for Polynomials. 

In order to get a clear idea of the problem, we shall begin by 
considering the case where f(x) = a + <h x + t hf^ + • • ■ + °n a! " 
is itself a polynomial of the ra-th degree. We can then easily 
express the coefficients of this polynomial in terms of the deri- 
vatives of f(x) at the point x = 0. For if we differentiate both 
sides of the equation once, twice, &c, with respect to x and 
then put x = 0, we at once find that the coefficients are 

«o =/(0). <h =/'(0), a 2 = I /"(0), .... «„ = I /« (0). 

Any polynomial f(x) of the n-th degree can therefore be written 
in the form 

/(*) =/(0) + */'(0) + |j /"(0) + ^/'"(0) + . . . + ^>>(0). 

This formula merely states that the coefficients a„ can be ex- 
pressed in terms of the derivatives at x = and gives the 
expressions for them. 

We can generalize this " Taylor series " for the poly- 
nomial slightly if we replace x by f = x -\- h and consider 
the function /(£) =/(«+ h) = g(h) as a function of h, for 

* A special case of this theorem is often referred to, without historical 
justification, as Maclaurin's theorem. We shall not follow this usage. 



VI] TAYLOR'S THEOREM 321 

the moment thinking of x as fixed and h as the independent 
variable. It then follows that 

and hence, if we put A = 0, 

<7'(0) =/'(*), ..., <? n) (0)=f\x). 

If we apply the previous formula to the function/(a; + h) = g(h), 
which is itself a polynomial of the w-th degree in h, we im- 
mediately obtain the Taylor series 

h 2 h 3 

fit) =/(* + h) =/(*) + */'(*) + I /"(*) + !/"'(*) + . . . 

2. Taylor's Theorem for an Arbitrary Function. 

These formulae suggest that we should seek a similar formula 
in the case of an arbitrary function f{x), not necessarily a 
polynomial; in this case, however, the formula can lead only 
to an approximation to the function by a polynomial. 

We wish to compare the values of the function/ at the point 
x and at the point £ = x + h, so that h = $ — x. If now n is 
any positive integer whatever, the expression 

/(*) + ($- x)f(x) + ... + (i^LV'to 

will not, as a rule, be an exact expression for the functional value 
/(I). We must therefore put 

m =/(*) + a - *)/'(*) + ( -^p^/"(*) + . • . 

+ ( i^!/W(*) + R n , 

where the expression R„ denotes the remainder when /(£) is 
replaced by the expression f(x) +f'(x) (f — x) + . . . . In the 
first instance this equation is nothing but a formal definition of 
the expression R n . Its significance lies in the fact that we can 
easily find a neat and useful expression for this remainder R n . 
For this purpose we think of the quantity £ as fixed and the 



332 TAYLOR'S THEOREM [Chap. 

quantity x as the independent variable. The remainder is then 
a function R n (x). By the above equation this function vanishes 
for x = £: 

R n (t) = o. 

Further, by differentiation, we obtain 

n! 

For if we differentiate the equation defining the remainder 
with respect to x, we obtain on the left, since /(£) does not 
depend on x and is therefore to be regarded as a constant. On 
the right we differentiate each term by the rule for products, 
and find that all the terms cancel out except the last one, which 
is written above with a minus sign. 

Now by the fundamental theorem of the integral calculus 

R n (x) = R n (x) - R n (i) = fR n '(t)dt= fR„'(t)dt, 

so that we obtain the formula 

RM = f +h {x + h ~ t)n f +1 Ht)dt. 

Jx n! 

If we introduce a new variable of integration r by means of the 
equation t = t — x, this becomes 

R„=^f o \h- t)»/ (b+1) (s + r)dr. 

Collecting these results, we have the following statement: 
If the function f(x) has continuous derivatives up to the 
(n -f- l)-th order in the interval under consideration, then 

/(* + h) =/(*) + hf\x) + *J/"(s) + £/'"(*) + . . . 

+ ljf (n Hx) + R«, 

or (the equivalent expression for h = £ — x) 

/(€) =/(*) + (£- x)f(x) + <l^lf"(x) + . . . 



2! 



+ { -^f^f M (x) + R« 



VI] TAYLOR'S THEOREM 323 

where the remainder Rn is given by the formula 

R « = ~, C ( A - T) n f ln+1 Hx + r)dr. 

If in particular we put x = and then replace h by x, we 
obtain the formula 

/(*) =/(0) + J/'(0) + p"{0) +... + *j>>(0) + i?» 

with the remainder 

«-=-. f"(x-TW +1 >(r)&r. 

These formula are known as Taylor's theorem. They give 
expressions for the functions f(x + h) and f(x) respectively in 
terms of polynomials of degree n in h and in x respectively (the 
so-called polynomial of approximation), and a remainder. The 
polynomial of approximation is characterized by the fact that 
when h = (or x = 0, as the case may be) its value and 
that of its first n derivatives are the same as those of the 
given function and its first n derivatives. In contrast 
with the Taylor series for polynomials * the remainder and the 
expression for it are essential here. The significance of the 
formula lies in the fact that the remainder, even though it 
has a more complicated form than the other terms of the 
formula, nevertheless affords us a useful means for estimating 
the accuracy with which the sum of the first n + 1 terms, 

/(0) + J/'(0) + ~f"(0) +... + J/ (B) (0), 

represents the function/(x). 

3. Estimation of the Remainder. 

Whether the first n + 1 terms of Taylor's series actually give 
a sufficiently good approximation to the function naturally 
depends on whether the remainder is sufficiently small. We 
therefore now turn our attention to the estimation of this re- 
mainder. Such an estimate can most easily be made by means 
of the mean value theorem of the integral calculus (Chap. II, § 7, 
p. 127). 

* Whose representation requires no remainder. 



334 TAYLOR'S THEOREM [Chap. 

We use this theorem in the form 

f"p(r) <f>{r) dr = <f>{6h) f" p(r) dr, 

JQ Jq 



where p(r) is a continuous function which is nowhere negative 
in the interval of integration, and ^(t) is merely a continuous 
function there, while 6 is a number in the interval * 5S 6 5S 1. 
If in the formula for the remainder we take (h — t) b to be p(r) 
we obtain 

*-(^V' + "<»+<»); 

while if instead we put p(r) = 1 we obtain the expression 
£» = ^ r (l-0)"/ (n+1) (s+0A) J 

which is less important for us and is stated here only for the sake 
of completeness. In these formulae 6 denotes a certain number 
in the interval ^ 6 ^ 1, whose value we cannot in general 
specify more accurately; as a rule, of course, this value is dif- 
ferent in the two formulae for the remainder, and in addition 
depends on n, x, and h. The first form of the remainder was 
given by Lagrange, the second by Cauchy, and they are 
correspondingly named.j- 

Our interest will be directed chiefly towards finding out 
whether the remainder R„ tends to zero as n increases; if this is 
the case, the larger we choose n the more accurately is f(x + h) 
represented by the corresponding polynomial in h. In this case 

* We may in fact assume that < d < 1, but this is of no importance 
here. 

t These expressions for the remainder, as well as others, can be derived 
from the mean value theorem of the differential calculus and from the general- 
ized mean value theorem (p. 203) respectively. We apply these theorems to 
the function R M (z) = S„(x) — B n (£) and to the pair of functions B n (x) and 
(x — £ )" +1 respectively, where we consider ( as fixed and make use of the formula 

R»'X*) - - {i ~ , !t) " / ( » +1> (!g). 

These methods of deriving the formulas for the remainder throw more stress on 
the fact that Taylor's theorem is a generalization of the mean value theorem; 
they also offer the advantage, which for many theoretical purposes is important, 
that we need only assume the existence and not the continuity of the (» + l)-th 
derivative. On the other hand, however, we lose the advantage of having an 
exact expression for the remainder in the form of an integral. 



VI] TAYLOR'S THEOREM 325 

we say that we have expanded the function in an infinite Taylor 
series 

/(* + *) =/(*) + *,/'(*) + |/"(*) + ?f"(z) +..., 

or, in particular, if we first put x = and then write x in place 
of h, 

/(*) =/(0) + £/' (0) + p" (0) + p'" (0) + . . . . 

We shall meet with examples of this in the next section. 

First, however, we wish to point out the second important 
point of view arising from consideration of Taylor's series. 
If in the first formula we think of the quantity k as becoming 
smaller and tending to zero, then in the terminology of Chap. Ill, 
§ 9 (p. 195), the various terms of the series will tend to zero 
with different orders of magnitude; we accordingly call the 
expression f(x) the term of zero order in Taylor's series, the 

12 
expression hf'(x) the term of first order, the expression — /" (x) 

2i\ 

the term of second order, and so on. From the form of our 
remainder we see the following fact: 

In expanding a function as far as the term of n-th order we make 
an error which tends to zero with order (n + 1) as h -»■ 0. 

On this fact many important applications depend. It shows 
us that the nearer the point x + h lies to the point x, the better 
is the representation of the function f(x + h) by the polynomial 
of approximation, and that in a given case the approximation 
in the immediate neighbourhood of the point x can be improved 
by increasing the value of n. 



Examples 

1. Let /(*) have a continuous derivative in the interval agi^l, 
and let J"(x) ^ for every value of x. Then if 5 is any point in the inter- 
val, the curve nowhere falls below its tangent at the point x = Z,,y = /(!;)• 
(Use the Taylor expansion to three terms.) 

2. Find the value of in Lagrange's form of the remainder B n for the 

expansions of and in powers of x. 

1 — x 1 + x 



336 TAYLOR'S THEOREM [Chap. 

3. Applications. Expansions of the Elementary 
Functions 

We shall now use the general results of the preceding section 
in order to express the elementary functions approximately by 
means of polynomials and to expand them in Taylor series. 
We shall, however, restrict ourselves to those functions for which 
the coefficients of the expansion in series are given by simple 
laws of formation. The series for certain other functions will 
be discussed in Chap. VIII (p. 405 et seq.). 

1. The Exponential Function. 

The simplest example is offered by the exponential function, 
f(x) = e*. Here all the derivatives are identical with f{x) and 
therefore have the value 1 for x = 0. Hence by using Lagrange's 
form for the remainder we at once obtain the formula 



1! 2! ' 3! ' n! (n+l)l 

in accordance with § 2 (p. 320 et seq.). If we now let n increase 
beyond all bounds the remainder will tend to zero, no matter 
what fixed value of x we have chosen. For | e e * | ^ e 1 *' to begin 
with. We now choose a fixed integer m greater than 2 | x |. 
Then f or n ~2i m we have 



n < 2' 



a-n+i 



(n + 1)! 



35™ 



m\ m-\- 1 



^ \x m \ 1 ^ |2a;| m 1 

— m \ 2"+ 1 -™ — m! 2 B ' 



so that \R n \ ^ I ^ I" el*! 1. 

1 ' _ m! 2" 

Since the first two factors on the right are independent of n, 
while the number 1/2" tends to zero as n increases, our state- 
ment is proved. If we think of the number x not as fixed, but 
as free to vary in the interval — a ^ x ^ a, where a is a fixed 
positive number, it follows from the above that if we choose 
m > 2a the estimate 

IT? |<£l 2a l"«- 1 



VI] SERIES FOR ELEMENTARY FUNCTIONS 327 

is valid provided n^m. For the remainder we have therefore 
specified a bound which holds for all values of a; in the interval 
— a^x^a, and which tends to zero as n -*■ 00. For the func- 
tion e x we can therefore write the expansion as an infinite series 

V n.% /».3 » — V 

1! 2! 3! >.ov! 

the last expression being merely an abbreviated expression for 
the series. This expansion is valid for all values of x. Thus we 
have again proved that the number e considered in Chap. I 
(cf. p. 43) is the same as the base of the natural logarithms 
(cf. Chap. Ill, § 6). For numerical calculations we must, of course, 
make use of the finite form of Taylor's theorem with the re- 
mainder; for x = 1, for example, this gives 

c = 1 + l + 1 + 1+ . . . + 1 + — il— 
2! 3! »! (n+ 1)! 

If we wish to calculate e with an error of at most 1/10,000, we 

need only choose n so large that the remainder is certainly less 

than 1/10,000; and since this remainder is certainly less * than 

3/(n + 1)!, it is sufficient to choose n = 7, since 8! > 30,000. 

We thus obtain the approximate value 

e = 2-71822 

with an error less than 0-0001. Here we do not take any account 

of the error due to neglecting the figures in the sixth decimal place. 



2. Sin:*;, cos a;, 


sinhx, cosh a:. 






For the functions sin a;, 


cos a;, sinha;, 


cosh a; we 


find the follow- 


ing formulae: 


t 










/(*) 


= 


sin a; 


cos a; 


sinha; 


cosh a;, 


/'(*) 


== 


cos a; 


— sin a; 


cosh a; 


sinha;, 


/"(*) 


= 


— sin a; 


— cos a; 


sinha; 


cosh a;, 


/'"(*) 


= 


— cos a; 


sin a; 


cosh a; 


sinha;, 


f v W 


= 


sin a; 


cos a; 


sinha; 


cosh a;. 



* Here we have made use of the fact that e < 3. This follows immediately 

(of. p. 43 also) from our series for e; for it is always true that _ ^ T , and 

therefore *■'■ 2 "~ 1 

e<l + l+i+i+ ... = 1 + 1/(1 - i) - 3. 

•f If f(x) — sina; or f(x) — cos*, the n-th derivative can always be repre- 
sented by the expression 

/<»'(X) - f(X + i«77). 



328 TAYLOR'S THEOREM [Chap. 

Hence in the polynomials of approximation for sin a; and sinha: 
the coefficients of the even powers of x vanish, while in the poly- 
nomials of approximation for cos a; and cosh a; the coefficients of 
the odd powers vanish. Thus in the first case the (2w + l)-th 
and the (2w + 2)-th polynomials are identical, while in the 
second case the 2n-th and the (2n + l)-th are identical. If in 
each case we use the higher of these polynomials we at once 
obtain, using Lagrange's form of the remainder, 

a? . x 5 . , . _. n x 2n+1 

sinx = x — —. + ~-. (-••• + (—1)" 



3! 5! ■ x / ( 2w+ i)l 

T 2n+3 

+ ( - 1)n+1 ^+l)! C08( ^ 
cosa;=l -%+^-+ ... + (_i)- * 



2! 4! ' (2m)! 

~2n+2 

+ (— l)"* 1 — . cos (to), 

^ v ' (2n+2)! v * 

X 3 X 5 X 2n+1 

sinha; = x+ — + -- + .. .+ 



3! 5! (2w+l)! 

x 2n+3 

4- cosh (to), 

^(2n+3)! v * 

, . . a; 2 x* x 2 » 

cosha;=l + - + - + . .. + _ 

/g2n+2 

+ cosh (to), 

(2w+2)! v * 

where in each of the four formulae, of course, 9 denotes a different 
number in the interval ^ 6 ^ 1, a number which in addition 
depends on n and on x. In these formulas we can also make the 
approximation as exact as we please for each value of x, since 
the remainder tends to as n increases. We thus obtain the 
four series 

x 3 , x? , " ..„ a; 2 "* 1 

sina; = x — - + ]-... = !• (— 1) 



3! ' 5! r - (2v + 1)! 

cos* = l_* +£_+.. . = S (-1)'* 
2! 4! „=o (2v)! 



VI] SERIES FOR ELEMENTARY FUNCTIONS 329 



4*3 4*5 

sinha; =x+ — + — + 
3! 5! 


V ^ 

,_o(2v+l)!' 


X 2 X* 

cosh a; = 1 + — + — + 
2! 4! 


S a 2 " 
• • • — ^ ,„ ..' 
,_o(2v)l 



The last two can also be obtained formally from the series for 
e* in accordance with the definitions of the hyperbolic functions. 

3. The Binomial Series. 

We may pass over the Taylor series for the functions log (1 -f- a;) 
and arc tana;, which have already been treated directly in § 1 
(p. 315). We must, however, take up the generalization of the 
binomial theorem for arbitrary indices, which is one of the most 
fruitful of Newton's mathematical discoveries, and which repre- 
sents one of the most important cases of expansion in Taylor 
series. Our object is the expansion of the function 

f(x) = (1 + xT 

in a Taylor series, where x > — 1 and a is an arbitrary number, 
positive or negative, rational or irrational. We have chosen the 
function (1 + x) a instead of af because at the point x = it is 
not true that all the derivatives of a;* are continuous, except in 
the trivial case of non-negative integral values of a. We first 
calculate the derivatives of f(x), obtaining 

fix) = 0(1 + *rs /"(*) = 0(0 - 1) (i + xy-\ . . . , 

/'>(*) = a(a - 1) . . . (a - v + 1) (1 + xf~\ 
In particular, for x = we have 

/'(0) = a, /"(0) = a(a - 1), . . . , /«(0) = a(a - 1) (a - v + 1). 
Taylor's theorem then gives 

(l + *)«=l + a»+^jli ) ^-r-... 

a(a-l)(a-2)...(a-n+l) ^ R ^ 

We have still to discuss the remainder. This problem is not very 
difficult, but nevertheless is not quite so simple as in the cases 
treated previously. Here we shall pass over the estimation of 
the remainder, since the general binomial theorem will be proved 



33° TAYLOR'S THEOREM [Chap. 

completely in a somewhat different and simpler way in Chap. 
VIII (p. 406 et seq.; cf. also p. 336). The result, which we 
mention here in advance, is that whenever | x | < 1 the re- 
mainder tends to and therefore the expression (1 4- x) a can 
be expanded in the infinite binomial series 

» + ">'- I + D'+ :S T i, *+--!.(*V' 

where for brevity we have introduced the general binomial 
coefficients Q = <*(*- *)• • >~ "+ D (for „ > 0)> M = L 

Examples 

1. Expand (1 + x)l to two terms plus remainder. Estimate the re- 
mainder. 

2. Use the expansion of Ex. 1 (discarding the remainder) to calculate 
V2. What is the degree of accuracy of the approximation? 

3. What linear function best approximates to <y/(l + x) in the neigh- 
bourhood of x = 0? Between what values of x is the error of the approxi- 
mation less than -01? 

4. What quadratic function best approximates to -^(l + x) in the 
neighbourhood of x = 0? What is the greatest error in the interval 
—0-1 ^ x g 0-1? 

5. (a) What linear function, (6) what quadratic function, best approxi- 
mates to -\/(l + x) in the neighbourhood of x = 0? What are the greatest 
errors when — -1 g x 5j -If 

6. Calculate sin (-01) to 4 places. 

7. Do the same for (a) cos (01), (6) -^126, (c) \/97. 

8. Expand sin (x + h) in a Taylor series in h. Use this to find sin 31° 
(= sin (30° + 1°)) to 3 places. 

Expand the functions in Ex. 9-18 in the neighbourhood of x = to 
three terms plus remainder (writing the remainder in Lagrange's form). 
9. sin 2 !. 14. «-*'. 

15. -L. 

cos a: 



10. 


cos 8 *. 


11. 


log cos*. 


12. 


tan i. 


13. 


log 

oosz 



16. cot a; ■ 

17. -L- 



sinz 



lg log(l + x) 
1 + x 



VI] SERIES FOR ELEMENTARY FUNCTIONS 331 

19. (a) Expand e sln * to five terms plus remainder; (5) in the power 
series for e* substitute for z the power series for sin a;, taking enough terms 
to secure that the coefficient of x* is correct. Compare with (a). 

20. Find the polynomial of fourth degree which best approximates to 
tanx in the neighbourhood of x = 0. In what interval does this polynomial 
represent tana; to within 5 per cent? 

21. Find the first 6 terms of the Taylor series for y in powers of x 
for the functions defined by 

(a) x* + y* = y, y(0) = 0; (6) 7? + y* = y, y(0) = 1; 
(c) r> + y» = y, y(0) = 0. 

4. Geometrical Applications 

The behaviour of a function f(x) in the neighbourhood of a 
point x = a, or the behaviour of a given curve in the neigh- 
bourhood of a point, can be studied with increased accuracy by 
means of Taylor's theorem, for this theorem resolves the increment 
of the function on passing to a neighbouring point x = a-\-h into 
a sum of quantities of the first order, second order, &o. 

1. Contact of Curves. 

We shall now make use of this method in order to investi- 
gate the concept of contact of two curves. 

If at a point, say the point x = a, two curves y = f(x) and 
y=g(x) not only intersect, but also have a common tan- 
gent, we shall say that at this point the curves touch one another 
or have contact of the first order. The Taylor expansions of the 
functions f(a-\-h) and g(a-\-h) then have the same terms 
of zero order and of first order in h. If at the point x = a 
the second derivatives of f(x) and g(x) are also equal to one 
another, we say that the curves have contact of the second order. 
In the Taylor expansions the terms of second order are then 
also the same, and if we assume that both functions have con- 
tinuous derivatives of the third order at least, the difference 
D(x) =f{x) — g{x) can be expressed in the form 

D(a + h ) =/(o + h) - g(a + h) = | D'" (a + 9h)= ^F(h), 

where the expression F(h) tends to /'"(a) — g'"{a) as h tends to 
zero. The difference D(a-{-h) therefore vanishes to at least 
the third order with h. 



33* 



TAYLOR'S THEOREM 



[Chap. 



We can proceed in this way and consider the general case, 
where the Taylor series for f(x) and g(x) are the same up to terms 
of the w-th order, that is, 

/(«) = 9 («),/'(«) = <f («),/"(«) = *"(«), • • • ./ (B) («) = (?*(»)■ 

We here assume that the (» + l)-*h derivatives are also continuous. 
Under these conditions we say that at this point the curves have 
contact of the n-th order. The difference of the two functions will 
then be of the form 

/(a + h) - g(a + h) = ^-^ F(h), 




Fig. i. — Osculating parabolas of e* 

where since ^ B ^ 1 the quantity F (h) = & n+ti (a + 0h) 
tends to f n+1) (a) — g (n+1) (a) as h tends to 0. We recognize 
from this formula that at the point of contact the difference 
f(x) — g{x) vanishes to the (n + l)-th order at least. 

The Taylor polynomials are simply defined geometrically by 
the fact that they are those parabolas of the w-th order 
which at the given point have contact of the highest possible 
order with the graph of the given function. Hence they are 
sometimes called osculating parabolas. For the case y=e x 
fig. 1 gives us the first three osculating parabolas at the point 
a;=0. 

If two curves y=f{x) and y = g(x) have contact of the 
ra-th order, the definition does not exclude the possibility that 



VI] GEOMETRICAL APPLICATIONS 333 

the contact may be of still higher order, i.e. that the equation 
/<" +1 >(a) = $r< B+1) (a) is also true. If this is not the case, i.e. if 
/ (B+1) (o) =j= fif (B+1) (a), we speak of a contact of exactly the n-th 
order or say that the order of the contact * is exactly n. 

From our formulae as well as from our figures we can at once 
state a remarkable fact which is often unnoticed by beginners. 
If the contact of two curves is exactly of an even order, that is, 
if an even number ra of derivatives of the two functions have the 
same value at the point in question, while the (w + l)-th deri- 
vatives differ, then in conformity with the above formulae the 
difference f(a + h) — g(a -\- h) will have different signs for small 
positive values of h and for numerically small negative values 
of h. The two curves will then cross at the point of contact. 
This case occurs e.g. in contact of the second order if the third 
derivatives have different values. If, however, we consider the 
case of contact exactly of an odd order, e.g. the case of an or- 
dinary contact of the first order, the difference f(a + h) — g (a + h) 
will have the same sign for all numerically small values of h, 
whether positive or negative; the two curves therefore will 
not cross in the neighbourhood of the point of contact. The 
simplest example of this is the contact of a curve with its tan- 
gent. The tangent can cross the curve only at points where the 
contact is of the second order at least; it will actually cross the 
curve at points where the order of contact is even, e.g. at an 
ordinary point of inflection, where /" (a;) = but /'" (x) 4= 0. 
At points where the order of contact is odd it will not cross 
the curve; as examples we may take an ordinary point of the 
curve where the second derivative is not zero, or the curve 
y = sb 4 at the origin. 

2. The Circle of Curvature as Osculating Circle. 

When looked at from this point of view the concept of the 
curvature of a curve y =f(x) gains a new intuitive significance. 
Through a definite point of the curve with the co-ordinates 
x = a, y = 6 there pass an infinite number of circles which 
touch the curve at the point. The centres of these circles 
lie on the normal to the curve, and to each point of this normal 

* That the order of contact of two curves is a genuine geometrical relation 
which is unaffected by change of axes is a fact which can easily be established 
by means of the formula for change of axes. 




334 TAYLOR'S THEOREM [Chap. 

there corresponds just one such tangent circle. We may expect 
that by proper choice of the centre of the circle we can bring 
about a contact of the second order between the curve and the 
circle. 

As a matter of fact, we know from Chap. V (p. 283) that for 
the circle of curvature at the point x = a, whose equation is, say, 
y = g(x), we not only have g («)=/(») and g'(a)=f'{a), 
but also g"(a)=f"(a). Hence the circle of curvature is at 
the same time the osculating circle at the point of the curve 
under discussion; that is, it is the circle which at that point has 

contact of the second order 
'^ /^" \ with the curve. In the 

limiting case of a point of 
inflection, or in general of 
a point at which the cur- 
vature is zero and the 
radius of curvature is in- 
finite, the circle of curva- 
ture degenerates into the 
tangent. In ordinary cases, 
that is, when the contact 
at the point in question 
does not happen to be of an order higher than the second, the 
circle of curvature will not merely touch the curve, but will 
also cross it (cf. fig. 2). 

3. On the Theory of Maxima and Minima. 

As we have already seen in Chap. Ill (p. 161), a point x = a 
at which/' (a) = gives a maximum of the function/(a;) if/" (a) 
is negative, a minimum if/" (a) is positive. These last conditions, 
therefore, are sufficient conditions for the occurrence of a maxi- 
mum or minimum. They are by no means necessary; for in the 
case where /" (a) = there are three possibilities open; at the 
point in question the function may have a maximum or a mini- 
mum or neither. Examples of the three possibilities are given 
by the functions y = — cc 4 , y = a; 4 , and y = x 3 at the point 
x = 0. Taylor's theorem at once enables us to make a general 
statement of sufficient conditions for a maximum or a minimum. 
We need only expand the function /(a + h) in powers of A; the 
essential point is then to find whether the first non-vanishing 



sr 



Fig. a. — Osculating circle 



VI] GEOMETRICAL APPLICATIONS 335 

term contains an even power of h or an odd power. In the first 
case we have a maximum or a mini mum according as the co- 
efficient of h is negative or positive; in the second case we have 
a horizontal inflectional tangent and neither maximum nor 
minim um. The reader may complete the argument for himself 
by using the formula for the remainder.* 

Examples 

1. What is the order of contact of the curves y = e* and y = 1 + * + 
i sin'a: at x = 0? 

2. What is the order of contact of y = sin 4 a; and y = tan 4 a; at x = 0? 

3. Determine the constants a, b, c, d in such a way that the curves 
y = e** and y = a cosa; + 6 sina; + c cos2a; + d sin2a; have contact of 
order 3 at x = 0. 

4. What is the order of contact of the curves 

x* + y* = xy, a? + y a = a: 
at their points of intersection? Plot the curves. 

5. What i» the order of contact of the curves 

s* + Z/ a = y x*=y 
at their points of intersection? 

6. The curve y = f(x) passes through the origin O and touches the 

a;-axis at O. Show that the radius of curvature of the curve at O is given 

x 3 
by p = Iim — . 
*->o2y 

7.* K is a circle which touches a given curve at a point P and passes 
through a neighbouring point Q of the curve. Show that the limit of the 
circle K as Q -*■ P is the circle of curvature of the curve at P. 

8.* R is the point of intersection of the two normals to a given curve 
at the neighbouring points P, Q of the curve. Show that, as Q -». P, R 
tends to the centre of curvature of the curve for the point P. (The centre 
of curvature is the intersection of neighbouring normals.) 

9.* Show that the order of contact of a curve and its osculating circle 
is at least three at points where the radius of curvature is a maximum or 
minimum. 

10. Determine the maxima and minima of the function y = er 11 *'. 
(See p. 336.) 

* The necessary and sufficient condition given previously (p. 161), how- 
ever, is more general and more convenient in applications, namely: provided 
the first derivative f'(x) vanishes at only a finite number of points, a necessary 
and sufficient condition for the occurrence of a maximum or minimum at one 
of these points is that the first derivative f'(x) changes sign as it passes through 
the point. 



336 TAYLOR'S THEOREM [Chap. 



Appendix to Chapter VI 

1. Example of a Function which cannot be expanded 
in a Taylor Series 

The possibility of expressing a function by means of a Taylor 
series with a remainder of the (n + l)-th order depends essen- 
tially on the differentiability of the function at the point in ques- 
tion. For this reason the function log a; cannot be represented 
by a Taylor series in powers of x, and the same is true of the 
function y/x, whose derivative is infinite at x = 0. 

In order that a function may be capable of being expanded 
in an infinite Taylor series, all its derivatives must necessarily 
exist at the point in question; this condition, however, is by no 
means sufficient. A function for which all the derivatives exist 
and are continuous throughout an interval still need not neces- 
sarily be capable of expansion in a Taylor series; that is, the 
remainder R„ in Taylor's theorem may fail to tend to zero as 
w increases, no matter how small the interval in which we wish 
to expand the function. 

The simplest, example of this phenomenon is offered by the function 
y = f(x) = e -1 '"* for a; =t= 0, /(0) = 0, which we have already considered 
in the appendix to Chap. Ill (p. 196). This function, with all its derivatives, 
is continuous in every interval, even at x = 0, and we have seen that at 
this point all the derivatives vanish, i.e. that / <n) (0) = for every value 
of ». Hence in Taylor's theorem all the coefficients of the polynomials 
of approximation vanish, no matter what value we choose for n. In other 
words, the remainder is and remains equal to the function itself, and 
therefore, except when % = 0, does not approach as n increases, since 
the function is positive for every non-zero value of x. 

2. Proof that e is Irrational 

From the formula e=2+- + ...-| + — eP, we immediately 

2! n! (n+ 1)! 

deduce that the number e is irrational. For if the contrary is true, that 

is, if e = p/q, where p and q are integers, we can certainly choose » 

larger than q. Then n!e = n\ - must be an integer. On the other hand, 

? 

»!e = 2»! + — + ...+ — + e e , and since e" < e < 3, we must 

21 nl n + 1 



VI] 



CONVERGENCE OF BINOMIAL SERIES 



337 



have < < 1. Hence the integer re!e = the integer 2re! + — + 

n + 1 * 

. . . + 1 plus a non- vanishing proper fraction, which is impossible. 



3. Proof that the Binomial Series Converges 

In § 3 (p. 329) we postponed the estimation of the remainder 
R n in the expansion of f(x) = (1 + xf for | x \ < 1. This 
estimation we shall carry out here. It is most convenient to 
separate the cases x > and x < 0. 

For/ ( " +1) (a;) we have the expression 

y^»(,) = o(«-l)...(a-»)^±^ i . 
If x > 0, we write the remainder in Lagrange's form, 



u / x x " +1 , i\ i \ ( l + 6x )' 

R n (x) = - — 1 — 7ri a(o — 1) . . . (a — n) 



so that 



*.(*) I ^ 



(n+l)I 

a(a — 1) ... (a — n) 



(n + 1)! 



(1 + Ox)"* 1 
x n +\l + x) a 

]n+l " 



Writing b = [ | a | ] + 1, where [ | a | ] means the greatest integer 
which does not exceed | a |, we have 

\R n (x)\^W±^p^} x » + i 
\n -\- L)i 

<Z 2 " l-2...(n+l)(n+2)...(»+6) %n+ i 
-(6-1)! (n+1)! 

2" 



— (n + 6)»-V+ x , 

(6-l)! v ; 



and since b is fixed, if < x < 1, this approaches as n 
increases. 

For the case —1 < x < we write the remainder in Cauchy's 
form, 

-* M1 a-«>-«<--i)...<«-»)< 1 + tora 



R„(X) : 

so that 



nl 



(1 + dx) n 



Iwli^pW 



a(a— l)...(a — n) 



12 



ia+ for 1 1 

(E798) 



338 TAYLOR'S THEOREM [Chap. 

Since \x\ < 1, the last factor cannot exceed a constant E, 
independent of n. Also (1 — d) / (1 — 8 1 x | ) < 1. As before, 
writing b = [ | a \ ] 4- 1, we have 

\R n (x)\ ^ K\x\">> —1— (n+ 2) (n+ 3) . . . (n + 6) 
(6 — 1)! 

^(T~Iji (n + 6)W|af,M1 » 

which approaches as n increases. 

Thus in either case when | x | < 1 the remainder tends to 
zero as n increases, justifying the expansion in § 3 (p. 330). 



4. Zekos and Infinities op Functions and So-called 
Indetebminate Expeessions 

The Taylor series for a function in the neighbourhood of a 
point x = a enables us to characterize the behaviour of the 
function in the neighbourhood of this point in the following way. 
We say that a function f(x) at x = a has an exactly n-twple zero 
or it vanishes there exactly to the order n, if f(a) = 0, J (a) = 0, 
f"(a) = 0, . . . , /'-"(a) = 0, and /<»>(<*) #= 0. Here we assume 
that in the neighbourhood of the point the function possesses 
continuous derivatives to the w-th order at least. By our de- 
finition we seek to indicate that the Taylor series for the function 
in the neighbourhood of the point can be written in the form 

in which as h ->- the factor F(h) tends to a limit different from 
0, namely, the value /"(a). 

If a function <f>(x) is defined at all points in the neighbour- 
hood of a point x = a, except perhaps at x = a itself, and if 

At \ f( x ) 

where at the point x = a the numerator does not vanish, but 
the denominator possesses a p-tuple zero, we say that the func- 
tion ^(aj) becomes infinite of the v-th order at the point x = a. 
If at the point x = a the numerator also possesses a /x-tuple 



VI] INDETERMINATE EXPRESSIONS 339 

zero and if /* > v, we say that the function has a (/* — v)-tuple 
zero there; while if (*.<.v we say that the function has a 
(v — /i)-tuple infinity. 

All these definitions are in agreement with the conventions 
already laid down (cf. Chap. Ill, § 9, p. 194) regarding the be- 
haviour of a function. In order to make these relations precise, 
we expand numerator and denominator by Taylor's theorem, 
using Lagrange's form of the remainder; the function then has 
the form 

Ma 4- h\- ^ a + *> - " ! ^ M(a + 6h) 

in which 8 and 8 1 are two numbers between and 1 and the 

factors by which — and — are multiplied do not tend to zero 
fil vl 

as h does, since they approach the limits / (,l) (a) and g^ v) (a) 

respectively, which differ from zero. If /x > v, we then have 

lim #> + A) = lim v l h»~ J ^ = 0. 



0/*! 



The expression cf>(x) accordingly vanishes to the order /i — v. 
If v> fi, we see that the expression <f>(a -f- h) becomes infinite 
of the order v — /u. as h -*■ 0. If jj. = v, we obtain the equation 

h-yO 9 {<*) 

We can express the content of the last equations in the fol- 
lowing way: if the numerator and denominator of a function 

Mx) = 1^1 both vanish at x = o, we can determine the limiting 

value as x -*■ a by differentiating the numerator and denominator 
an equal number of times until one at least of the derivatives is 
other than zero. If this happens for numerator and denominator 
simultaneously, the limit which we are seeking is equal to the 
quotient of these two derivatives. If we encounter a non-vanish- 
ing derivative in the denominator earlier than in the numerator, 
the fraction tends to zero. If we encounter a non-vanishing 
derivative in the numerator earlier than in the denominator, the 
absolute value of the fraction increases beyond all bounds. 



340 TAYLOR'S THEOREM [Chap. 

We thus have a rule for evaluating the so-called indeter- 
minate expression 0/0 — a subject that is discussed at exaggerated 
length in many textbooks on the differential and integral cal- 
culus. In reality the point in question is merely the very simple 
determination of the limiting value of a quotient in which the 
numerator and the denominator tend to zero. The name 
" indeterminate expression " usually found in the literature is 
misleading and vague. 

We can arrive at our results in a somewhat different way by 
basing the proof on the generalized mean value theorem * instead 
of on Taylor's theorem (cf. p. 135). According to this, if 
gf(x) 4= 0, we have 

f(a+h)-f(a) _ f'(a+eh) 
g(a+h)-g(a) g , (a+6h)' 

where 8 is the same in both numerator and denominator. 
Hence, in particular, when f(a) = = g(a), 

f(a+h) _ f'(a+6h) 
g(a + h) g'(a+6h)' 

Here is a value in the interval < 6 < 1, and if we put 
k = 6h, we obtain 

Una f^t+3 = lim ££±*>, 
h^-og(a + h) k^o g'(a + k) 

it being assumed that the limit on the right exists. If 
f'(a) = = g'(a), 

we can proceed in the same manner until we come to the first 
index for which it is no longer true that / w (a) =0=g w (a). 
Then 

lim /(^±i) =lim /^ + ^ 
h -+og(a + h) ,-+ g M (a + l) 

in which we also include the case in which both sides have the 
limit infinity. 

* This method of deriving our rule has the advantage that in it no use is 
made of the existence of the derivative at the point x = a itself: further, it 
includes the case in which 4>(x) is defined for x^2l a only, so that the passage 
to the limit x -*■ a or ft -»• is made from one side only. 



VI] INDETERMINATE EXPRESSIONS 341 

As examples we consider 

wax 1 — oosa; «*" — 1 x* tans 

T' x * log(l + x)' V(l - x>) - 1 

as x -» 0. We have 

.. sina: oosO . .. 1 — cosa: sinO „ 
lim = «=» 1; nm = — — = u; 

X 1 *-H> x 1 



dm = lim — ■ = 2; 

_.„ log(l + *) —9-0 1/(1 + x) 

x* tana; ,. 2x tana + a^/oos»i 

lim = lim - — - — 

._^„ </,'] - **) - 1 _h> -a;/V(l - a; 2 ) 

= -lim (2 tanas + -JL V(l - x*) = 0. 
^_».o V cos* a;/ 

We further note that other so-called indeterminate forms can also be 

reduced to the case we have considered; for example, the limit of - r — 

sinx x 

as x -»■ 0, being the limit of the difference of two expressions which both 
become infinite, is an " indeterminate form "00 — 00, By the trans- 
formation 

1 1 x — sina: 



we at once arrive at an expression whose limit as x -> is determined by 
our rule to be 

1 — cosx .. sina; n 

lim = hm : — = 0. 

«->o x coss -f sins «-h> 2 cosa: — x sm* 

Examples 

Evaluate the limits in Ex. 1-12: 

l.lim*^l n . 7. lim(-l__ 1\ 

,_ > . x — a *->i vb* — 1 x — 1/ 

2. lim *- sina: . 8. lim (4- - Y\. 
^.0 3? x-+o\am*x x*l 

n ,. 24 — 12a? + x* — 24 cosa; . .. . _ 

3. lim - 5 . 9. lima: 8 ' 11 *. 

(sina;) 6 *-»-o 



4. lim e °'~ er< '. 10. lim (1 + *)!/*. 

1— »-o sina; *— »-o 

6. lim?£2i^. "• Mm *" ~ * 



*_>o log(l + x) 



6. lim *5*L 12. lim xtmx 



«->.*« tanas" *-»-o V(l — 3?) — 1 

13. Prove that the function y — (a?)*, y(0) = 1 is continuous at 1 = 0. 



CHAPTER VII 
Numerical Methods 

Preliminary Kemarks 

Anyone who has to use analysis as an instrument for 
investigating physical or technical phenomena is faced by the 
question whether and how the theory can be adapted to yield 
useful practical methods for actual numerical calculations. Yet 
even from the point of view of the theorist, who desires only 
to recognize the connexions between natural phenomena, not 
to conquer them, these questions are of no trifling interest. 
For a systematic treatment of numerical methods we refer the 
reader to special textbooks on the subject.* Here we can only 
discuss some particularly important points which are more or 
less closely connected with the preceding ideas. We wish to 
direct special attention to the fundamental fact that the mean- 
ing of an approximate calculation is not precise unless it is 
supplemented by an estimate of the errors occurring, i.e. unless 
it is accompanied by definite knowledge of the degree of 
accuracy attained. 

1. Numerical Integration 

We have seen that even relatively simple functions cannot 
be integrated in terms of elementary functions and that it is 
futile to make this unattainable goal the aim of the integral 
calculus. On the other hand, the definite integral of a continuous 
function does exist, and this fact raises the problem of 
finding methods for calculating it numerically. Here we shall 
discuss the simplest and most obvious of these methods with 

* Cf. e.g. Whittaker and Robinson, The Calculus of Observations (Blackie & 
Son, Ltd., 1929). 

M2 



Chap. VII] NUMERICAL INTEGRATION 343 

the aid of geometrical intuition, and we shall then consider the 
estimation of errors. 

Our object is to calculate the integral I = / f(x)dx, where 

•'o 

a is less than 6. We imagine the interval of integration divided 
into n equal parts of length h = (b — a)ln, and we denote the 
points of subdivision by x = a, x^ — a + h, . . . , x„ = b, 
the values of the function at the points of division by /q, f v 
•••>/«> and similarly the values of the function at the mid- 
points of the intervals by / 1/2 , / 3/2 , . . . , / (2n _ 1)/2 . We interpret 
our integral as an area and cut up the region under the curve 
into strips of breadth h in the usual manner. We must now 
obtain an approximation for each such strip of surface, that is, 
for the integral 

f(x)dx. 



1. The Rectangle Rule. 

The crudest and most obvious method of approximating to I 
is directly connected with the definition of integral; we replace 
the area of the strip Z„ by the rectangle of area/, h and obtain 
for the integral I the approximate expression * 

I*>h(f + &+... +/„_!). 

2. The Trapezoid and Tangent Formulae. 

We obtain a closer approximation with no greater trouble if we 
replace the area of the strip Z„, not by the above rectangular area, 

but by the trapezoid of area - (/, -f f p+1 )h shown in fig. 1. For 

Z 

the whole integral this gives the approximate expression 

I * *(/l +/.+ ... +/»-!) + *(/,+/.) 

(the trapezoid formula), since, when the areas of the trapezoids 
are added, each value of the function except the first and the 
last occurs twice. 

* Here and hereafter the symbol «tf means " is approximately equal to ". 



344 



NUMERICAL METHODS 



[Chap. 



As a rule the approximation becomes even better if instead 
of choosing the trapezoid under the chord AB as an approxi- 
mation to the area of I we choose the trapezoid under the tan- 
gent to the curve at the point with the abscissa x = x„ -\- h/2. 
The area of this trapezoid is simply hf v+i , and the approxi- 
mation for the entire integral is 

I fin h(f m +f m + ... +/( 2n -i)/ 2 )» 

which is called the tangent formula. 




Fig. I. — The trapezoid formula 



3. Simpson's Bale. 

By means of Simpson's rule we arrive, with very little more 
trouble, at a numerical result which is generally much more 
exact. This rule depends on estimating the area I v -\- I v+1 of 
the double strip between the abscissse x = x v and x = x f + 2h 
= a5 v+ 2 by considering the upper boundary to be no longer a 
straight line but a parabola; to be specific, that parabola which 
passes through the three points of the curve with abscissae 
x *> x v+i = x v +h, and x v+2 = x y +2h (cf. fig. 2). The equation 
of this parabola is 

^ (x - x v ) (x-x v - h) f v+2 - 2/ r+1 +/, 
^ 2 # 



VII] 



NUMERICAL INTEGRATION 



345 



(The student may verify by direct substitution that for the 
three values of x in question this equation gives the proper values 
of y, namely, /„, /„ +1 , and/„ +2 respectively.) If we integrate 
this polynomial of the second degree between the limits x v and 
x v + 2 A, we obtain, after a brief calculation, the following ex- 
pression for the area under the parabola: 

j x ydx=2hf v +2h(f v+1 -/ r ) + ^|A-2AJ(/ r+a -2/, +1 +/ r ) 
= *(/,+4/H-i + /r+i). 




Fig. 2. — Simpson's rule 

This represents the required approximation to the area of our 
strip, /„ + I v+1 . 

If we now assume that w = 2m, i.e. that n is an even number, 
by the addition of the areas of such strips we obtain Simpson's 
rule: 

Ar}) 

'«* |(/i+/a + + .../ 2m - 1 ) 

+ -Q (/a +/» + +/2m-2) + 2 (/o +/am)- 



12 • 



(1708) 



346 NUMERICAL METHODS [Chap. 

4. Examples. 

— If 

1 x 
we divide the integral from 1 to 2 into ten equal parts, h will be equal 
to i^y, and by the trapezoid formula we obtain 



x 1 = 11 


/, = 0-90909 


x 2 = 1-2 


f 2 = 0-83333 


x 3 = 1-3 


/„ = 0-76923 


x t = 1-4 


U = 0-71429 


x 6 = 1-5 


ft = 0-66667 


x e = 1-6 


/„ = 0-62500 


x 7 = 1-7 


/, = 0-58824 


x s = 1-8 


f a = 0-55556 


x, = 1-9 


/„ = 0-52632 




Sum 618773 


x = 10 


hfo = 0-5 


x 10 = 2-0 


J/io = 0-25 




6-93773 X ^g 




log,2 ss 0-69377 



This value, as was to be expected, is too large, since the curve has its 
convex side turned towards the a;-axis. 
By the tangent rule, we have 

av, + lh = 1-05 /,/, = 0-95238 

Xl + \h = 1-15 /s /2 = 0-86957 

x s + $h = 1-25 / 5 / 2 = 0-80000 

x 3 + \h = 1-35 /,/, = 0-74074 

a; 4 + | A = 1-45 /„/, = 0-68966 

x, + \h = 1-55 /„/, = 0-64516 

*„ + \h = 1-65 jf ls /, = 0-60606 

x,+ lh= 1-75 / 15/l = 0-57143 

x g + lh = 1-85 / 17 / s = 0-54054 

*» + lh = 1-95 / 19 /ij =. 0-51282 



6-92836 X ^g 



log, 2 <sn 0-69284 
Owing to the convexity of the curve, this value is too small. 



VIIJ 



NUMERICAL INTEGRATION 



347 



For the same set of subdivisions we obtain the most exaot result by 



means of Simpson's rule. We have 



*, = 11 
*, = 1-3 
x t = 1-5 
x ? = 1-7 
x„ = 1-9 



/, = 0-90909 
/ 3 = 0-76923 
/ 5 = 0-66667 
/ 7 = 0-58824 
/, = 0-52632 

Sum 3-45955 X 4 

13-83820 



*,= 1-2 
x, = 1-4 
x 6 = 1-6 
z a = 1-8 



x,„ = 2-0 



/, = 0-83333 
/ 4 = 0-71429 
/, = 0-62500 
/„ = 0-55556 

Sum 2-72818 X 2 

5-45636 
13-83820 



20-79456 X 3*3 



As a matter of fact 



log. 2 f%) 0-69315 
log.2 = 0-693147 . . . 

5. Estimation of the Error. 

It is easy to give an estimate of the error in each of our 
methods of integration if the derivatives of the function f(x) 
are known throughout the interval of integration. We take 
M v M % , ... as the upper bounds of the absolute values of the 
first, second, . . . derivatives, respectively; that is, we assume 
that throughout the interval |/ w (x) | < M r . Then the estimation 
formulae are as follows: 

For the rectangle rule 



l^-A/J^M^or 
For the tangent rule 

K-V, +i |<§A3 or 
For the trapezoid rule 



I-AS/, 



<-M 1 nA2=-M 1 (6-a)A. 
2i 2i 



v=0 



< 



Mi 
24 



(6 -a) A 2 . 



j,-;;(/v+/h-i) 



< 



M 2 
12 



A 3 . 



For Simpson's rule 



■*» + *v+i — o (/" ~^~ V»+i +A+2) 



< 



90 



A 5 



348 NUMERICAL METHODS [Chap. 

From the last two estimates there also follow estimates for 
the entire integral I. We see that Simpson's rule has an error 
of much higher order in the small quantity h than the other 
rules, so that where M i is not too large it is very advantageous 
for practical calculations. To avoid wearying the reader with the 
details of the proofs of these estimates, which are fundamentally 
quite simple, we shall content ourselves with the proof for 
the tangent formula. For this purpose we expand the function 
f(x) in the (v + l)-th strip by Taylor's theorem: 

/<*>-/,+*+ (* - * - *)/'(** + i) + -J(—*- s)>(A 

where £ is a certain intermediate value in the strip. If we 
integrate the right-hand side over the interval x v ^ x £S x y -\- h, 
the integral of the middle term is zero. Since 



1 /■*+*/ A\» h 3 



as is easily verified, it follows immediately that 



ry+ll 
f(x)dx-Kf r . 

which proves our assertion. 



<*.£. 



Examples 



7r r 1 1 

1. From the formula - — I ; dx, calculate it 

4 J 1 + x 2 

(a) using the trapezoid formula with h = 0*1; 
(6) using Simpson's rule with h = 0-1. 

/•00 

2. Calculate / e-^'dx numerically to within y£ c (of. p. 496). 

r 1 1 

3. Calculate / , numerically with an error less than (H. 

J Vl + z 4 



VII] THE CALCULUS OF ERRORS 349 

2. Applications op the Mean Value Theorem and op 
Taylor's Theorem. The Calculus op Errors 

1. The " Calculus of Errors ". 

We now come to quite a different type of numerical calcu- 
lations. These are applications of the mean value theorem, or 
more generally of Taylor's theorem with remainder, or finally 
of the infinite Taylor series. As an application which, though 
simple, is quite important in practice we shall consider the cal- 
culus of errors. This rests upon the idea — which lies at the root 
of the whole of the differential calculus — that a function f(x) 
which is differentiable a sufficient number of times can be re- 
presented in the neighbourhood of a point by a linear function 
with an error of order less than the first, by a quadratic func- 
tion with an error of order less than the second, and so on. Let 
us consider the linear approximation to a function y=f(x). 
If y + Ay =f(x-\- Ax)=f(x-\- A), by Taylor's theorem we 
have 

Ay=hf'(x) + ^f"(i), 

where £ = x + dh(Q < <1) is an intermediate value, which 
need not be more precisely known. If h = Ax is small 
we obtain as a practical approximation 

Ay ps hf'{x). 

In other words, we replace the difference quotient by the deri- 
vative to which it is approximately equal and the increment of 
y by the approximately equal linear expression in A. 

We use this fairly obvious fact for practical purposes in the 
following way. Suppose two physical quantities x and y are 
connected by the relation y= f(x). The question then arises, 
what effect an inaccuracy in the measurement of x has on the 
determination of y. If instead of the " true " value x we happen 
to use the inaccurate value x -J- h, then the corresponding 
value of y differs from the true value y=f{x) by the amount Ay= 
f(x + A) — f(x). The error is therefore given approximately 
by the above relation. 



35° NUMERICAL METHODS [Chap. 

We shall understand the use of these relations better if we con- 
sider a few examples. 

Six. 1. The tangent galvanometer. In determining current by a tangent 
galvanometer we use the formula y = c tan a, where a is the angle of 
deflection of the magnetic needle, c is the constant of the apparatus, 
and y = I is the intensity of the current. Then 

dy _ e 
da cos* a 

and therefore Ay *%* — — Aa. The percentage error in the measurement 
is given by cos a 

lOOAy lOOcAa 200 A 
» f& ;^ = Aa. 

y c cos 2 a tan a sin 2a 

From this we see that the accuracy reaches the greatest possible value, 
Le. to a given error in the measurement of the angle there corresponds 




the least possible error in the determination of the current, when the 
angle a is equal to 7t/4 or 45°. 

In particular, let us suppose that it is possible to read the tangent gal- 
vanometer to within half a degree; then | Aa | in radians < J X 0-01745 . . . , 

and the percentage error will be — . If the reading on the galvano- 

sin2a 

meter is 30°, sin2a= J V3 =$ X 1-73205 ... , and the percentage 

error is less than 2 x , which is about 2 per cent. 

1-732 

Ex. 2. In a triangle ABO (of. fig. 3) we suppose that the sides b and e 
are measured accurately, while the angle a = x can only be measured 
with an error | Ax | < 8. Within what limit of error does the value 
y = o = Vfft* + c* — 26c cos a) vary? 

We have Aa fa - be sin a Aa; 

a 

«. 4 • a * lOOAa 1006<r . . T . , , ,. 
tne percentage error is therefore fa — — sin a Aa. If we take the 



VII] THE CALCULUS OF ERRORS 351 

special oase where 6 = 400 metres, c = 500 metres, and a = 60°, then 
by the cosine formula y = a = 458-2576 metres, and 

200000 w 1 .- 
Aa ^45¥2576 X 2 V3Aa - 
If Aa can be measured to within ten seconds of arc, that is, if 

Ace = 10" = 4848 X lO -8 radians, 
we find that at worst 

Aa pa 1-83 om.; 

that is, the error is at most about 0-004 per cent. 

Ex. 3. The following illustrates a type of application of the above 
methods by which we can often save ourselves considerable trouble in 
physical problems. 

It is known experimentally that if an iron rod has the length l at 
temperature 0, then at temperature t its length will be I = Z (l -+- <**)> 
where a depends only on the material of which the rod is made. If now 
a pendulum clock keeps correct time at temperature <,, how many 
seconds will it lose per day if the temperature rises to t t l 

For the period of oscillation we have the formula 

'9 & Vlg 

Hence if the change of length is Al the corresponding change in the 

period of oscillation is 

._, 7t Al 
AT & —_=, 

Via 

where ^ = l (l + otfj and Al = aZ (< 2 — h)- This is the time lost per 
oscillation. The time lost per second is AT/T s» Al/71^ hence in one day 
the clock loses 43200 Al/l t seconds. 

Here the application of our methods has saved us a number of multi- 
plications and two extractions of the square root. In the longer direct 
process, moreover, we should finally have to subtraot T(lj) from the almost 
equal value T(l 2 ), and a very small error in calculation would cause a rela- 
tively large percentage error in the result.* 

In this case, and in most cases where the function under consideration 
has several factors or fractional indices, we oan reduce the calculation 
even more by taking the logarithms of both sides before differentiating. 
In the present example we have 

logT = log2n — - log? + - log/; 
by differentiating, we have 

ill 2/ 

* It is a point of this nature that makes the calculations of applied optics 
so extremely laborious. 



T(V) = 2tzJ 1 -, whence % = -?L. 



352 NUMERICAL METHODS [Chap. 

dT AT 
If we replace — by — this gives 
dl Al 

AT ^ Al 
T 2f 
in agreement with the preceding result. 

2. Evaluation of n. 

Gregory's series,* ^ = 1 — - + _— --\ ..., which we 

obtained in Chap. VI, § 1 (p. 319) using the series for the inverse 
tangent, is not suitable for the calculation of -n, on account of 
the slowness of its convergence. We may, however, calculate 
ir with comparative ease by the following artifice. From the 
addition theorem for the tangent, 

. , , o\ tana + tanfi 

tan(a + ft = ^ H 

1 — tana tanp 

if we change to the inverse functions a = arc tan u, ft — arc tan v, 
we obtain the formula 



arc tanw -f- arc tanu = arc tan 



\1 — uv/ ' 



If we now choose u and v in such a way that — — — = 1, we 

1 — uv 

obtain the value - on the right-hand side, and if u and v are 
4 

small numbers we can easily calculate the left-hand side by 

means of known series. If, for example, we put u== -, v== -, 

as Euler did, we obtain 

— = arc tan - + arc tan -. 
4 2 3 

If we further notice that |- + -J-r(l — — ) = -, we have 

\3 7/ \ 21/ 2 

arc tan - = arc tan - + arc tan -, so that 
2 3 7 

— = 2 arc tan - + arc tan -. 
4 3^7 

Using this formula Vega calculated the number -n to 140 places. 

* Sometimes called Leibnitz's series. 



VII] CALCULATION OF LOGARITHMS 353 

By means of the equation (- + -)-i-(l — - ) = „, we 

J * \5 8/ \ 40/ 3 

further obtain 

arc tan - = arc tan - + arc tan 
3 5 8 

or 

- = 2 arc tan - + arc tan - + 2 arc tan -. 
4 5 7 8 

This expansion is extremely useful for the calculation of 

77 by means of the series arc tana; = x — — + — ["•••» f° r 

o 

if we substitute for x the value -, -, or - we obtain with but 

few terms a high degree of accuracy, since the terms diminish 
rapidly. We can, however, perform the calculation even more 
conveniently if we base it on the formula 

77 ,.120 . 1 , , 1 1 

— = arc tan — — arc tan — = 4 arc tan arc tan — , 

4 119 239 5 239 

obtained by considerations similar to those above. 

3. Calculation of Logarithms. 

For the numerical calculation of logarithms we transform 

the logarithmic series - log "*" = x-\- — + — — |— . . . ( | £c | -<; 1> 
2 1 — x 3 5 

where < x < 1 by the substitution 
1 + x _ p 2 



x= — 



1 — x p 2 — 1 2jp 2 — 1 

into the series 

lo 8P = s lo E(P — !) + s log(? + 1) + 



2 ovx- " 2 =>' ' 2p 2 — 1 

+ 3(2^-l)3 + '-- ' 

where 2p 2 — 1 > 1, that is, p 2 > 1. If p is an integer and p + 1 
can be resolved into smaller integral factors, this last series 
expresses the logarithm of p by the logarithms of smaller integers 



354 NUMERICAL METHODS [Chap. 

plus a series whose terms diminish very rapidly and whose sum 
can therefore be calculated accurately enough by use of only 
a few terms. From this series we can therefore calculate 
successively the logarithms of any prime number, and hence 
of any number, provided we have already calculated the value 
of log 2. 

The accuracy of this determination of log^» can be estimated 
more easily by means of the geometric series than from the 
general formula for the remainder. For the remainder R n of 
the series, i.e. the sum of all the terms following the term 

n(2p 2 - l)n ' we ^ 

R n < I (l\ l \ 1 \ \ 

(n+2)(2f- 1)«+ 2 \ T (2p 2 - l) 2 ^ (2y 2 - 1)* ^ ' ' 7 

1 1 



(w+ 2) (2j» a - 1)» " (2jo 2 — l) 2 — 1' 

and this formula immediately gives the required estimate of the 
error. 

Let us for example calculate log , 7, using the first four terms of the 
series. We have 

p = 7, 2p» - 1 = 97, 

log7 = 2 log2 + _ log3 + — + 1 + . . .: 
e 6n 2 6T 97 3.97» 

-i (%( 001030928, — ~ on 0-00000037, 



hence 



2 log2 fti 1-38629436, - log3 an 0-54930614; 



log.7 ** 1-94591015. 
Estimation of the error gives 



5.97' 97 a - 1 36 x 10» 

We must, however, note that each of the four numbers which we have added 
is only given to within an error of 5 x 10 _, ( so that the last place in the 
value of log 7 given above might be wrong by 2. As a matter of faot, 
however, the last place is right also. 



VII] CALCULATION OF LOGARITHMS 355 

Examples 

1. To measure the height of a hill, a tower 100 metres high on top of 
the hill is observed from the plain. The angle of elevation of the base of 
the tower is 42° and the tower itself subtends an angle of 6°. What are 
the limits of error in the determination of the height if the angle 42° is 
subject to an error of 1°? 

2. Calculate log, 2 to three decimal places by means of an expansion 
in series. 

3. Calculate log, 6 to six decimal places, using the values of log, 2 and 
log, 3 given in the text. 

4. Calculate n to five decimal places, using any one of the formulae in 
sub-section 2 (pp. 352-3). 



3. Numerical Solution of Equations 

In conclusion we shall add some remarks about the numerical 
solution of the equation f(x) — 0, where f(x) need not necessarily 
be a polynomial.* Every such numerical method is based on 
the plan of starting with some known approximation x of one 
of the roots and then improving this approximation. Whence 
this first approximation for the desired root of the equation is 
found, and how good the approximation is, do not particularly 
matter. We may perhaps take a rough guess as a first approxi- 
mation, or better, obtain it from the graph of the function 
V =f( x )> whose intersection with the as-axis gives the required 
root (of course with an error depending on the scale and the 
accuracy of the drawing). 

1. Newton's Method. 

The following procedure which comes down to us from New- 
ton is based on the fundamental principle of the differential 
calculus — the replacing of a curve by a straight line, the tangent, 
in the immediate neighbourhood of the point of contact. If we 
have an approximate value x for a root of the equation /(x) = 0, 
we consider the point on the graph of the function y=f(x) 
whose co-ordinates are x — x , y =f(x ). What we wish to find 
is the intersection of the curve with the a^axis; as an approxi- 
mation to this we find the point where the tangent at the point 

•Here, of oourse, we are only concerned with the determination of real 
roots of /(as) - 0. 



35 6 



NUMERICAL METHODS 



[Chap. 



x — x , y=f(x ) intersects the sc-axis. The abscissa a^ of this 
intersection of the tangent with the a;-axis will then represent 
a new and, tinder certain circumstances, a better approximation 
than x to the required root of the equation. 

In virtue of the geometrical 

meaning of the derivative, fig. 4 

at once gives 

J^L=f(x ). 

x x^ 

From this we obtain the formula 
for the calculation of the new 
approximation a^: 




Fig. 4. — Newton's method of 
approximation 



X 1 - 



x n — 



/'W 



If by this procedure we have found an approximation bettei 
than x , then we repeat the process to find x 2 , and so on, and 
if the curve is of the form shown in fig. 3 these approximations 
will approach more and more nearly to the required solution. 




Fig. 5 



The usefulness of this process depends essentially on the 
nature of the curve y =f(x). In fig. 4 we see that the successive 
estimates converge with greater and greater accuracy to the 
required root. This is due to the fact that the curve has its convex 
side turned towards the »-axis. But in fig. 5 we see that if we 
choose the original value x badly, our construction does not 
lead to the required root at all. From this we see that in using 
Newton's method we must examine each individual case to 



VII] NUMERICAL SOLUTION OF EQUATIONS 357 

determine with what degree of accuracy we have really solved 
the equation. We shall return to this subject on p. 359. 

2. The Role of False Position. 

Newton's method, in which the tangent to the curve plays 
a decisive part, is only the limiting case of an older method, 
known as the rule of false position, in which the secant appears 
in place of the tangent. Let us 
assume that we know two points 
(z > Vo) and (ai. yi) in the neigh- 
bourhood of the required intersec- 
tion with the a^axis. If we replace 
the curve by the secant joining 
these two points the intersection 
of this secant with the x-axis will 

certain circumstances be an 



in 




Fig. 6. — The rule of false position 



improved approximation to the 

required root of the equation. 

If the abscissa of this point is denoted by £, we have (fig. 6) 

the equation 

i — 3p _ £— a?i 
and from this we calculate £: 

_ Sp/fa) — »h/(So) + Sp/fop) — 3j/(Zo ) 

/fro) 

{/to)— f( x o)}K x i — * )' 



or 



!=Zp 



This formula, which determines the further approximation | 
from x and a^, is called the rule of false position. We can use it 
with advantage if one value of the function is positive and the 
other negative, say as in fig. 6, where y > and y t < 0. Eepe- 
tition of this process will always lead us to the required result 
if at each step we use a positive and a negative value of the 
function, between which the required root must necessarily lie. 



358 NUMERICAL METHODS [Chap. 

The above formula of Newton results from the rule of false 
position as a limiting case if we let x 1 tend to x . For the 
denominator of the second term on the right-hand side of the 
statement of the rule of false position tends to f'(x ) as a^ 
tends to x . 

3. The Method of Iteration. 

Another means of approximation to the roots of an equation 
f(x) = is the method of iteration. Here we put <f>(x) =/(*) + x 
and write our equation in the form x = <f>(x). We then suppose 
that | is the true value of a solution of our equation, and x 
a first approximation. We obtain a second approximation x 1 
by putting x 1 — c/>(x ), a third approximation x 2 by putting 
x 2 = (^(xj), &c. To investigate the convergence of these approxi- 
mations, we apply the mean value theorem; recalling that 
£= 4>(£)> we have 

f - a* = *(fl - <£(*„) = d - x )<J>' (?) 
where f lies between £ and x . This shows that if for 
\t-x\<\t-x \ 

the derivative <f>'(x) is less in absolute value than k < 1, then 
the successive approximations converge, for 

| £ — X! | < k | | — x Q |, \£ — x 2 \<k*\£ — x \,..., 
\£-x a \<k»\£-x \, 

and the errors therefore tend to zero. The smaller the absolute 
value of the derivative </>'(x) near g, the more rapid is the con- 
vergence. 

If <f>'{x) > 1 in the neighbourhood of f the approximations 
no longer tend to £. We can then use the inverse function or 
else the following device. We choose a first approximation x , 
calculate A =f'(x ), and write 

<f>(x)=-~f(x) + x. 

Then the equation f(x) = can be written x = <j>{x), and here 

<f>'(x) = — t/'(x) + 1, which has the value at x = x and 
A 

hence will usually be less in absolute value than a constant 

k<l if \£- X \<\$-T. \. 



VII] NUMERICAL SOLUTION OF EQUATIONS 359 

Keturning to Newton's method, we can now investigate its suit- 
ability for application at any given point. The equation/(a;) = is 

equivalent to x = <f>(x) = x — ~J-, provided that f'(x) =j= 0. 

/to) 
Applying the method of iteration to this last equation, from a 

• 1 • 1 /too) 

first approximation x we obtain a second, a^ = x — ~ — - ; in 

/ too) 
other words, the same second approximation as Newton's method 
gives when applied to the equation f(x) = 0. We thus see that 
the smaller the value of 

9(> (/'to)) 2 ' 

the more rapidly do the successive approximations converge. 
In words, Newton's formula converges rapidly for large values 
of f'(x ) and small values of f(x ) and the curvature, as intui- 
tion would lead us to suspect. 

We can also obtain an estimate of the accuracy of Newton's 
method, if we recall that, since /(f) = 0, the derivative <f>'(i) = 0. 
Applying Taylor's theorem, we have 

I - *i = #(fl - <f> too) = ^=^ 2 r (& 

where g lies between f and x . Thus, if the error of the original 
estimate is small, the method converges much more rapidly than 
the method of iteration applied directly to f(x) — 0. 
For example, if 

^m _ {nx)yf"^)+f'^)f(x)f"(x)-2f(x){f"(x)Y 
9 v ' {/'to)} 8 

is everywhere less than 10, then a first approximation which is 
in error by less than -001 will yield a second approximation 
with an error of less than (-001) 2 X 10 -f- 2 = -000005. 

4. Examples. 

As an example we consider the equation 

/(*) = a? — 2x — 5 = 0. 

For x a ■= 2, we have /(a; ) = — 1, while for a^ = 2-1 we have /(a^) «= 0-061. 
By Newton's method, 

* " * - m = 21 ~ 3W^2 - 21 - - 005431 = 2 - 094569 - 



360 NUMERICAL METHODS [Chap. 

To estimate the error we find from the expression (a) above that <f"(x) 
is about 1 and certainly less than 2 near x = 2. Moreover, the error of 
our first approximation is certainly less than 1/160, for the secant joining 
the points x= 2, y= — 1 and x = 2-1, y= -061 cuts the i-axis at a 
distance less than 1/160 from x = 2-1, and the curve, lying under the 
secant, cuts it even nearer 2-1. So the error * of our second approximation 
is less than 

1 • — ?— = — — < -00004. 

2 (160) a 25,600 

If this degree of accuracy is not sufficient, we can repeat the process, 
calculating /(a^) and /'(a; a ) for x t = 2-094569, and obtain a third approxi- 
mation x. with an error less than < -000000002. 

(25,600)» 

As a second example, let us solve the equation f(x) = x log 10 a: — 2 = 0. 
We have /(3) = —0-6 and /(4) = +0-4, and therefore use x = 3-5 as a 
first approximation. Then by using ten-figure logarithmic tables we 
obtain the successive approximations 



x l = 3-598 

*, = 3-5972849 

x 3 = 3-5972850235. 

Examples 

1. Using Newton's method, find the positive root of x* + 6x — 8 = 
to four decimal places. 

2. Find to four places the root of x = tana; between n and 2tt. Prove 
that the result is accurate to four places. 

3. Using Newton's method, find the value of x for which 

1 



r 

Jq 



du = 



Jo l + « 2 2 

4. Find the roots of the equation x = 2 sin x to two places. 

5. Determine the positive roots of the equation xfi — x — 0-2 = 
by the method of iteration. 

6. Determine the least positive root of x* — 3a; 3 + 10a; — 10 = by 
the method of iteration. 

7. Find the roots of x 3 — 7x* + 6a; + 20 = to four decimal places. 

•Another way of estimating the error, without referenoe to the secant, is 
as follows: if we estimate that the error is less than 1/20, the error of our second 
approximation is less than 1/20' — -0025. Hence the root differs from 2-1 by 
less than (2-1 - 2-0945) + -0025 - -008. Therefore the error was not merely 
less than 1/20, but less than -008, so that x 2 is in error by less than (-008)* — 
■000064. 



VII] STIRLING'S FORMULA 361 

Appendix to Chapter VII 

Stirling's Formula 

In very many applications, especially in statistics and in the 
theory of probability, we find it necessary to have a simple 
approximation to n! as an elementary function of n. Such an 
expression is given by the following theorem, which bears the 
name of its discoverer Stirling: 

Asn-voo _ __ > 1; 

V2iTn n+i e-" 

more exactly, 

■s/2^n n+i e- n <nl< V2^n n+i e-"(l + j-\ 

In other words, the expressions n\ and "v / 27rw n+i e"" 1 differ 
only by a small percentage when the value of w is large — as we 
say, the two expressions are asymptotically equal — and at the 
same time the factor 1 + l/4n gives us an estimate of the degree 
of accuracy of the approximation. 

We are led to this remarkable formula if we attempt to 
evaluate the area under the curve y = log a;. By integration 
(p. 220) we find that A n , the exact area under this curve 
between the ordinates x = 1 and x = n, is given by 



/ logxdx = x logx — x 



n logn — » + 1. 



If, however, we estimate the area by the trapezoid rule, erecting 
ordinates at x = 1, x = 2, . . . , x = n as in fig. 7, we obtain 
T„, an approximate value for the area: 

T„ = log2 + log3 + . . . + log(n - 1) + \ logn 

= logn! — - logn. 

If we make the reasonable assumption that A„ and T„ are 
of the same order of magnitude, we find at once that n! and 
n n+i e -n are f £jj e game order of magnitude, which is essentially 
what is stated in Stirling's formula. 



362 NUMERICAL METHODS [Chap. 

To make this argument precise, we first show that the difference 
o n = A n — T„ is bounded, from which it will immediately follow 

that T H = A„ 1 1 — — " J is of the same order of magnitude as A n . 
\ AJ 




The difference a k+1 — a k is the difference between the area under 
the curve and the area under the secant in the strip k <S x ^ k + 1. 

Since the curve is concave down- 
ward and lies above the secant, 
a k+1 — a k is positive, and a n = 

(Of. — On-l) + («n-l — «n-2) +• • • + 

(o 2 — a x ) + a r is monotonic in- 
creasing. Moreover, the difference 
a k +x — a k is clearly less (cf. fig. 
8) than the difference between 
the area under the tangent at 

x = k 4- - and the area under the secant: hence we have 
2 

the inequality 

a*+i - a k < logU + y\ - * logfc - - log(fe + 1) 

= 1 Iogfl + r)- 1 log(l+ 1 ) 
2 g V + W 2 g V 2(k+y 




< 



l M i+ i)-l he ( i+ w+i)- 



VII] STIRLING'S FORMULA 363 

If we add these inequalities for k = 1, 2, . . . , n — 1, all the 
terms on the right except two will cancel out, and (since a^ — 0), 
we have 

«- < \ l °gl ~ hog (l + -^ < - log -. 

2 6 2 2 g \ 2w/ 2 8 2 

Hence a„ is bounded, and being monotonic increasing it 
tends to a limit a as n ->■ », Our inequality for a k+1 — a k now 
gives us 

a — a„ = S (a t+1 — a*)< - log( 1 + - ). 
*=« 2 \ 2n/ 

Since by definition A n — T„= a n , we now have 
logn! = 1 — a„ + (n + - j logw — n, 

or, writing a„ = e 1-0 ", 

n! = a n n n+ *e"~". 

The sequence a„ is monotonic decreasing and tends to the limit 
a = e L ~ a ; hence 

1< 5? = e a -°- < e * , °«< 1 + 1 ' 2 ''> = /A H- 1^ < l + A 

Hence we have 

an n+i e -n < n ! < an n +*e- n ( 1 + — V 

It only remains for us to find the actual value of the limit a. 
Here we make use of the formula proved in Chap. IV, § 4 (p. 225): 

V77 = lim W2*« 



„_ >0 o(2n)! y/ri 

Replacing n! by a„n n+ *e _n and (2n)! by o 2 „2 2n +*n 2n+i e- 2B , 
we immediately obtain 

yir = Iim — 2.— = , 

n ->- 00 a2„ V 2 a-y/2 

whence a = ^Jlit. The proof of Stirling's formula is thus com- 
pleted. 



364 NUMERICAL METHODS [Chap. VII 

In addition to its theoretical interest, Stirling's formula is a 
very useful tool for the numerical calculation of n! when n is 
large. Instead of multiplying together a large number of 
integers, we have merely to calculate Stirling's expression 
by means of logarithms, which involves far fewer operations. 
Thus for n = 10 we obtain the value 3598696 for Stirling's 
expression (using seven-figure tables), while the exact value of 
10! is 3628800. The percentage error is barely § per cent. 



Example 
Prove that lim V—L = _. 



CHAPTER VIII 

Infinite Series and Other Limiting 
Processes 

Preliminary Remarks 

The geometric series, Taylor's series, and a number of special 
examples which we have already met in this book suggest that 
we may well study those limiting processes which are called the 
summation of infinite series from a rather more general point of 
view. From its nature any limiting value 

S= lims„ 

n->oo 

can be written as an infinite series; for if n takes the values 
1, 2, 3, . . . , we need only put a„ = s„ — s„_ t for n > 1 and 
Oj = s x to obtain 

«n = <h + a 2 + ••• + «»> 

and the value 8 thus appears as the limit of s n , the sum of n 
terms as n increases. We express this fact by saying that S is 
the " sum of the infinite series " 

«i + «2 + a a + 

Thus an infinite series is simply a way of representing a 
limit where each successive approximation is found from the 
preceding by adding one more term. The expression of a number 
as a decimal is in principle merely the representation of a number 
a in the form of an infinite series a = Oy + a 2 -J- a 3 + . . . , 
where, if ^ a <^ 1, the term a„ is put equal to a„ X 10 -n and 
a„ is a whole number between and 9 inclusive. Since every 
limiting value can be written in the form of an infinite series, it 
may seem that a special study of series is superfluous. But in 
many cases it happens that limiting values occur naturally in 

885 



366 INFINITE SERIES [Chap. 

the form of infinite series, which often exhibit particularly simple 
laws of formation. Of course it is not true that every series has 
an easily recognizable law of formation. For example, the number 
it can certainly be represented as a decimal, yet we know no 
simple law enabling us to state the value of an arbitrary digit, 
say the 7000th, of this decimal. If, however, we set aside the 
representation of it by a decimal and consider Gregory's series 
instead, we have an expression with a perfectly clear general 
law of formation. 

Analogous to infinite series, in which the approximations to 
the limit are found by repeated addition of new terms, are 
infinite products, in which the approximations to the limit 
arise from repeated multiplication by new factors. We shall 
not go deeply into the theory of infinite products, however; the 
principal subject of this chapter and of the following chapter 
will be infinite series. 



1. The Concepts op Convergence and Diveegence 

1. The Fundamental Ideas. 

We consider an infinite series whose " general term " we 
denote * by o m ; the series is then of the form 

00 

<h. + a 2 + • • • = ^ a y 
i—l 

The symbol on the right with the summation sign is merely aD 
abbreviated way of writing the expression on the left. 
If as n increases the n-th partial sum 

n 

«n = <h + a 2 + • • • + a o == ^ a„ 

r—1 

approaches a limit 

S = lim»„ 

II— >00 

we say that the series is convergent, otherwise we say that it is 
divergent. In the first case we call S the sum of the series. 

We have already met with many examples of convergent 

* For formal reasons we include the possibility that certain of the numbers 
On may be zero. If all the a„'s from a number JV onward (i.e. when n> N) vanish, 
we speak of a terminating series. 



VIII] CONVERGENCE AND DIVERGENCE 367 

series; for instance, the geometric series 1 + q + q 2 -f- , 

which converges to the sum 1/(1 — q) when | q j < 1, Gregory's 
series, the series for log 2, the series for e, and others. In the 
language of infinite series, Cauchy's convergence test (cf . Chap. I, 
§ 6, p. 40) is expressed as follows: 

A necessary and sufficient condition for the convergence of a 
series is that the number 

I *m — s„ I = I a„ +1 -f a n+2 + . . . -f a m | 

becomes arbitrarily small if m and n are chosen sufficiently large 
(m > n). In other words: A series converges if, and only if, the 
following condition is fulfilled: if a positive number e is given, 
no matter how small, it is possible to choose an index N = N(e), 
which in general increases beyond all bounds as e -> 0, in such a 
way that the above expression | s m — s n | is less than e, provided 
only that m > N and n > N. 

We can make the meaning of the convergence test clearer by consider- 
ing the geometric series where q= i. If we choose e = t 1 ^, we need only 
takeiV=4. For 



JL( 1 + L+ +_U< 1 

jjn-i \2 ^ 2 a 2™-"/ 2 n - 



2»-» 

and Jl < JL if n > 4. 

2»-i 10 

If we choose e equal to T £ 5 , it is sufficient to take 7 as the corresponding 
value of N, as may easily be verified. 

Obviously it is a necessary condition for the convergence of a 
series that 

lim a n = 0. 

n— >■» 

Otherwise the convergence criterion certainly cannot be fulfilled. 
But this necessary condition is by no means sufficient for con- 
vergence; on the contrary, it is easy to find infinite series whose 
general term a n approaches as n increases, but whose sum does 
not exist, as the partial sum s n increases without limit as n 
increases. 



368 INFINITE SERIES [Chap 

An example of this is the series 

1 +-7^+-7»+--- + J- + 

V2 V3 Vn 

the general term of which is — ,— . We immediately see that 

V» 

,„> _L+... + J_ = » -V«. 
V» vn vn 

The n-th partial sum increases beyond all bounds as n increases, and 
therefore the series diverges. 

The same is true for the classic example of the harmonic series 

. + ! + ! + ! + .... 

=-*^+-+"--irn+— +s > s + — + s - l- *" 

n and m = 2n can be taken as large as we please, the series diverges, 
for Cauchy's test is not fulfilled; in fact, the n-th partial sum obviously 
tends to infinity, since all the terms are positive. On the other hand, the 
series formed from the same numbers with alternating signs, 

1 1 + 1 _ 1 + 1 -+ -|- <- iy ~ + 

converges (cf. Chap. VI, p. 317), and has the sum log2. 

It is by no means true that in every divergent series s„ tends 
to +00 or — oo . Thus, in the case of the series 

1-1 + 1-1 + 1 + - .... 

we see that the partial sum s„ has the values 1 and alternately, 
and on account of this oscillation backwards and forwards 
neither approaches a definite limit nor increases numerically 
beyond all bounds. 

With regard to the convergence and divergence of an infinite 
series the following fact which, though self-evident, is very im- 
portant, should be noted. The convergence or divergence of a series 
is not changed by inserting a finite number of terms or by removing 
a finite number of terms. So far as convergence or divergence is 
concerned, it does not matter in the least whether we begin the 
series at the term a , or o^ or a b , or any other term chosen 
arbitrarily. 



VIII] CONVERGENCE AND DIVERGENCE 369 

2. Absolute Convergence and Conditional Convergence. 

The series 1 -\ !-- + -••• diverges; but if we change 

the sign of every second term the resulting series converges. On 

the other hand, the geometric series 1 — q + q 2 — q 3 -\ ••• 

converges and has the sum 1/(1 -f q), provided that ^ q < 1; 
and on making all the signs plus we obtain the series 

l + q+q 2 + q*+..., 

which is also convergent, having the sum 1/(1 — q). 

Here there appears a distinction which we must examine a 
little more closely. With a series whose terms are all positive there 
are only two possible cases; either it converges or the partial 
sum increases beyond all bounds as n increases. For the partial 
sums, being a monotonic increasing sequence, must converge if 
they remain bounded. Convergence occurs if the terms approach 
zero rapidly enough as n increases; on the other hand, diver- 
gence occurs if the terms do not approach zero at all or if they 
approach zero too slowly. In series where some terms are 
positive and some negative, however, the changes of sign may 
bring about convergence, since a too great increase in the partial 
sums, due to the positive terms, is compensated by the nega- 
tive terms, so that the final result is that a definite limit is 
approached. 

00 

In order to grasp this fact the better, with a series 2 a v having 

positive and negative terms we compare the series which has 
the same terms all with positive signs, that is, 

KI + |« 2 | + ... = 2K|. 

••—I 

If this series converges, then for sufficiently large values of n 
and m > n, the expression 

I «n+l I + I °n+2 I + • • • + I «m I 

will certainly be as small as we please; on account of the relation 

I «n+l + • • • + a m I ^ I «n+l I + • • • + I «m I 
13 (B798) 



37° INFINITE SERIES [Chap. 

the expression on the left is also arbitrarily small, and so the 

original series S a v converges. In this case the original series is 

said to be absolutely convergent. Its convergence is due to the 
numerical smallness of its terms and does not depend on the 
change of the signs. 

If, on the other hand, the series with all the terms taken 
positively diverges and the original series still converges we say 
that the original series is conditionally convergent. Conditional 
convergence results from the terms of opposite signs compen- 
sating one another. 

For conditional convergence Leibnitz's convergence test is 
frequently useful: 

If the terms of a series are of alternating sign and in addition 
their absolute values | a n | tend monotonically to (so that 

00 

I Vul < | a |), the series £ a„ converges. (Example: Gregory's 

series (p. 352)). 

In the proof we assume that a 1 > 0, which does not essentially 
limit the generality of the argument, and write our series in the 
form 

W — &2 + \ (-•••» 

where all the terms b„ are now positive, b n tends to 0, and the 
condition b n+x < b n is satisfied. If we bracket the terms 
together in the two ways 

&l-(&2-& 3 )-(&4-& 5 )---. 

and (b 1 -b 2 )+(b s -b i )+(b 5 -b 6 )+... 

we see at once that the two following relations are satisfied 
by the partial sums: 



s l > S S > s i > • • • > s 2m+l > • • 
®2 <. S4 <Z S 6 <. . . . < S 2m < . . . 



On the other hand, s 2 „ < s 2n+1 < s t and s 2n+1 > s 2n > s 2 . The 
odd partial sums s 1; s 3 , ... therefore form a monotonic decreasing 
sequence, which in no case falls below the value s 8 ; hence this 
sequence possesses a limit L (p. 61). The even partial sums 
s 2 , s t , . . . likewise form a monotonic increasing sequence whose 



VIII] CONVERGENCE AND DIVERGENCE 371 

terms in no case exceed the fixed number s v and therefore this 
sequence must have a limiting value L '. Since the numbers s 2n 
and s 2n+1 differ from one another only by the number b %n+1 
which approaches as n increases, the limiting values L and II 
are equal to one another. That is, the even and the odd partial 
sums approach the same limit, which we now denote by S (cf. 
fig. 1). This, however, implies that our series is convergent, as 
was asserted; its sum is S. 

In conclusion, we make another general remark about the 

fundamental difference between absolute convergence and con- 

00 

ditional convergence. We consider a convergent series 2<v 

1—1 

We denote the positive terms of the series by p x , p 2 , p 3 , . . . , 

and the negative terms by — q v —q 2 , —q 3 , .... If we form the 

n-th partial sum s n — 2 a v of the given series, a certain number, 
say n', of positive terms and a certain number, say n", of nega- 

S 

o o o — J — 0000 e 

S2 S4 S 6 S s S g S 7 Sj 5j Sf 

Fig. 1. — Convergence of an alternating aeries 

tive terms must appear, where ri + n" = n. Further, if the 
number of positive terms as well as the number of negative terms 
in the series is infinite, then the two numbers n' and n" will 
increase beyond all bounds as n does. We see immediately that 

n' 

the partial sum s„ is simply equal to the partial sum 2 p v of the 

n" 

positive terms of the series plus the partial sum — £ q v of the 
negative terms. If the given series converges absolutely, then 

00 

the series of positive terms S p r and the series of absolute values 

00 
of the negative terms 2 q v certainly both converge. For as m 

v = l 

m m 

increases the partial sums 2 p„ and 2 q y are monotonic non- 

1/— 1 K = l 

CO 

decreasing sequences with the upper bound 2 | o, I. 

»— 1 
The sum of an absolutely convergent series is then simply equal 
to the sum of the series consisting of the positive terms only plus the 



373 INFINITE SERIES [Chap. 

sum of the series consisting of the negative terms only, or, in other 
words, is equal to the difference of the two series with positive terms. 

n ri n" 

For 2 a, — S p v — 2 q v ; as n increases n' and n" must also 

pml 11=1 V=l 

increase beyond all bounds, and the limit of the left-hand side 
must therefore be equal to the difference of the two sums on 
the right. If the series contains only a finite number of terms of 
one particular sign the facts are correspondingly simplified. If, 
on the other hand, the series does not converge absolutely, but 

oo CO 

does converge conditionally, then the series 2 p„ and 2 q„ must 

both be divergent. For if both were convergent the series would 
converge absolutely, contrary to our hypothesis. If only one 

diverged, say 2 p v , and the other converged, then separation into 

positive and negative parts, s„ = 2 p v — 2 q„, shows that the 

series could not converge; for as n increases n' and 2 p v would 

■-=1 

*" 
increase beyond all bounds, while the term 2 q v would approach 

a definite limit, so that the partial sum s„ would increase beyond 
all bounds. 

We see, therefore, that a conditionally convergent series cannot 
be thought of as the difference of two convergent series, the one con- 
sisting of Us positive terms and the other consisting of the absolute 
values of its negative terms. 

Closely connected with this fact there is another difference 
between absolutely and conditionally convergent series which 
we shall now briefly mention. 

3. Rearrangement of Terms. 

It is a property of finite sums that we can change the order 
of the terms or, as we say, rearrange the terms at will without 
changing the value of the sum. The question arises, what is the 
exact meaning of a change of the order of terms in an infinite 
series, and does such a rearrangement leave the value of the sum 
unchanged? While in the case of finite sums there is no difficulty, 
for example, in adding the terms in reverse order, in the case of 
infinite series such a possibility does not exist; there is no last 



VIII] CONVERGENCE AND DIVERGENCE 373 

term with which to begin. Now a change of order in an infinite 
series can only mean this: we say that a series Oj + a% -\- a 3 + • • • 
is transformed by rearrangement into a series b 1 -\-b i -\-b 3 -\- . . . , 
provided that every term a n of the first series occurs exactly 
once in the second and conversely. For example, the amount by 
which a„ is displaced may increase beyond all bounds as n does; 
the only point is that it must appear somewhere in the new series. 
If some of the terms are moved to later positions in the series, 
other terms must, of course, be moved to earlier positions. For 
example, the series 

1 + ? + ? a + ? 4 + f+ q* + q 7 + q* + f + ? 16 + . . . 

is a rearrangement of the geometric series 1 + q -\- q 2 + . . . . 

With regard to change of order there is a fundamental dis- 
tinction between absolutely convergent series and conditionally 
convergent series. 

In absolutely convergent series rearrangement of the terms does 
not affect the convergence, and the value of the sum of the series is 
unchanged, exactly as in the case of finite sums. 

In conditionally convergent series, on the other hand, the value 
of the sum of the series can be changed at will by suitable rearrange- 
ment of the series, and the series can even be made to diverge if 



The first of these facts, referring to absolutely convergent 
series, is easily established. Let us assume to begin with that our 
series has positive terms only, and let us consider the w-th partial 

n 

sum s n = 2 a„. AH the terras of this partial sum occur in the 

m 

m-th partial sum t m = S 6„ of the rearranged series, provided 

only that m is chosen large enough. Hence t m ^ s n . On the 
other hand, we can determine an index n' so large that the 

n" 

partial sum s n . = S a„ of the first series contains all the terms 

b v 6 2 , . . . , b m . It then follows that t m 5S s„. sS A, where A is 
the sum of the first series. Thus for all sufficiently large values 
of m we have s„ iS t m g A; and since s„ can be made to differ 
from A by an arbitrarily small amount, it follows that the 
rearranged series also converges; and in fact to the same limit 
A as the original series. 



374 INFINITE SERIES [Chap. 

If the absolutely convergent series has both positive and 
negative terms, we may regard it as the difference of two series 
each of which has positive terms only. Since in the rearrange- 
ment of the original series each of these two series merely under- 
goes rearrangement and therefore converges to the same value 
as before, the same is true of the original series when rearranged. 
For by the case just considered the new series is absolutely 
convergent and is therefor© the difference of the two rearranged 
series of positive terras. 

To the beginner the fact just proved may seem a triviality. That it 
really does require proof, and that in this proof the absolute convergence is 
essential, can be shown by an example of the opposite behaviour of con- 
ditionally convergent series. We take the familiar series 

1,11,11,11, .„ 

1 — - + - —_ + _—-+_ — --\ ... = log2. 

2 3 4 5 6 7 8 
under it write the result of multiplication by the factor -, 

+ - — - H ... = - logZ, 

2 4 6 8 2 s ' 

and add, combining the terms placed in vertical columns.* We thus obtain 

i, 1 1,1.1 1,1,1 1 , , 3, „ 

1 + -— - + - + - H-H — - + H ...= - log2. 

3 257 4911 6 2* 

This last series can obviously be obtained by rearranging the original 
series, and yet the value of the sum of the series has been multiplied by 
the factor 3/2. It is easy to imagine the effect that the discovery of this 
apparent paradox must have had on the mathematicians of the eighteenth 
century, who were accustomed to operate with infinite series without 
regard to their convergence. 

We shall give the proof of the theorem stated above concern- 
ing the change in the sum of a conditionally convergent series 
which arises from change of order of the terms, although we shall 
have no occasion to make use of the result. Let p v p z , . . . be the 
positive terms and — q lt —q 2 , . . . the negative terms of the 
series. Since the absolute value | a n | tends to as n increases, 
the numbers p u and q n must also tend to as n increases. As 



* For the addition of series see No. 4, p. 376. 



VIII] CONVERGENCE AND DIVERGENCE 375 

we have already seen, moreover, the sum* Ep, must diverge, 

00 
and the same is true of 2<7„. 
1 
Now we can easily find a rearrangement of the original series 

which has an arbitrary number a as limit. Suppose, to be specific, 

that a is positive. We then add together the first n^ positive 

terms, just enough to secure that the sum Sp„ is greater than a. 

Since the sum Sp y increases with n^ beyond all bounds, it is 

always possible by using enough terms to make the partial 
sum greater than a. The sum will then differ from the exact 
value a by p ni at most. We now add just enough negative terms 

— 2a„ to ensure that the sum 2j>„ — Sg„ is less than o; this 

1 11 » 

is also possible, as follows from the divergence of the series Eg,. 

The difference between this sum and a is now q mj at most. We 

"i 
now add just enough other positive terms S p v to make the 

partial sum again greater than a, as is again possible, since the 
series of positive terms diverges. The difference between the 
partial sum and a is now p„ t at most. We again add just 

IK, 

enough negative terms — 2 q r , beginning next after the last 

one previously used, to make the sum once more less than a, 
and continue in the same way. The values of the sums thus 
obtained will oscillate about the number a, and when the process 
is carried far enough the oscillation will only take place between 
arbitrarily narrow bounds; for since the terms p„ and q v them- 
selves tend to when v is sufficiently large, the length of the 
interval in which the oscillation takes place will also tend to 0. 
The theorem is thus proved. 

In the same way we can rearrange the series in such a way 
as to make it diverge; we have only to choose such large 
numbers of the positive terms as compared with the negative 
that compensation no longer takes place. 

* This abbreviated notation for S p y , and analogous expressions for 

x=l 

other series, will often be used in future. 



376 INFINITE SERIES [Chap. 

4. Operations with Infinite Series. 

It is clear that two convergent infinite series a t -f- a 2 -f . . . = S 
and b x + b 2 + . . . = T can be added term by term, that is, 
that the series formed from the terms c n = a n + b u converges 
and has the value S + T for its sum.* For 

Sc„= £a y +ib v -+S+T. 

v""l v=l l"»l 

It is also clear that if we multiply each term of a convergent 
infinite series by the same factor the series remains convergent, 
its sum being multiplied by the same factor. 

In the cases just mentioned it is immaterial whether the 
convergence is absolute or conditional. On the other hand, 
further study, which is not necessary for us here, shows that 
if two infinite series are multiplied together by the method 
used in multiplying finite sums together, the product series 
will not usually converge or have the product of the two sums 
for its sum unless at least one of the two series is absolutely 
convergent (cf. appendix, p. 415). 

Examples 

1. Prove that S =-L + -!_ + _L + ...= i. 

,-iv(v+l) 1.2 T 2.3 3.4 

2. Prove that 5 - = I. 

v-iv(v+l)(v+2) 4 

3. Prove that S (— 1)» 2v + 3 = I 

,-o (v+l)(v + 2) 

4. For what values of a does the series 1— i-f-2— 1-f 
converge? 2 " 3« 4° 

5.* Prove that if S a„ converges, and s n = % + a t + . . . + a„, then 
the sequence " -1 

«i + % + • • • + s s 

N 

also converges, and has S o F as its limit. 

6. Is the series 2 ( ] convergent? 

»-i \2n +1 2ra / 

7. Is the series 2 (—1)" — — convergent? 

*-i v + 1 

* This theorem is really nothing more than another statement of the fact 
(cf. Chap. I, § 6, p. 41) that the limit of the sum of two terms is the sum of 
their limits. 



VIII] CONVERGENCE TESTS 377 



2. Tests for Convergence and Divergence 

We have already met with a test of a general nature for the 
convergence of series, which applies to series with terms of alter- 
nating signs and decreasing absolute value and which asserts 
that such series are at least conditionally convergent. In the 
following pages we shall only consider criteria referring to absolute 
convergence. 

1. The Comparison Test. 

All such considerations of convergence depend on the com- 
parison of the series in question with a second series; this second 
series is chosen in such a way that its convergence can readily 
be tested. The general comparison test may be stated as follows: 

If the numbers b v b 2 , . . . are all positive and the series S b, 
converges, and if '-1 

\a n \^b n 

CO 

for all values of n, then the series 2 a n is absolutely convergent. 

n=l 

If we apply Cauchy's test the proof becomes almost trivial. 
For if m 2> n, we have 

I a n + . . . + a m I ^ I o„ I + . . . + I a m | ^ b n + . . . + b m . 

Since the series £ b n converges, the right-hand side is arbitrarily 

»=i 
small, provided that n and m are sufficiently large. It follows 
that for such values of n and m the left-hand side is also arbi- 
trarily small, so that by Cauchy's test the given series converges. 
The convergence is absolute, since our argument applies 
equally well to the convergence of the series of absolute values 
Kl- 

The analogous proof for the following fact can be left to the 
reader. If 

\a„\^b n >0, 



"■* 00 

and the series 2 b n diverges, then the series 2 a n is certainly not 
absolutely convergent. 

13 * (B798) 



378 



INFINITE SERIES 



[Chap. 



2. Comparison with the Geometric Series. 

In applications of the test the comparison series most 
frequently used is the geometric series. We at once obtain the 
following theorem: 

QO 

The series S a n w absolutely convergent if from a certain term 

onward a relation of the form 

Kl<c? B (I) 

holds, where c is a positive number independent of n and q is any 
fixed positive number less than 1. 

This test is usually expressed in one of the following weaker 

QO 

forms: the series 2 a„ converges absolutely, if from a certain 

n=l 

term onward a relation of the form 



a n+l 



<? 



(Ila) 



holds, where q is again a positive number less than 1 and inde- 
pendent of w, or: if from a certain term onward a relation 
of the form 



v | «n | < q (IK) 

holds, where q is a positive number less than 1. In particular, 
the conditions of these tests are satisfied if a relation of the 
form 

a n+l 



lim 



k<l 



or 



lim V | a n \ = k < 1 



(Ilia) 



(UK) 



is true. These statements are easily established in the following 
way. 

Let us suppose that the criterion Ila, the ratio test, is satisfied 
from the suffix n onward, that is, when n > n . For brevity 
we put a„ o+m+1 = b m and find that 

IM<slM> IM<<zlM<2 2 IM> \b*\«i\h\«r , \b \, 

and so on; hence 

l&«l<rlM. 



VIII] CONVERGENCE TESTS 379 

which establishes our statement. For the criterion 116, the 
root test, we at once have | a„ | < q n , and our statement follows 
immediately. 

Finally, in order to prove criterion III, we consider an arbi- 
trary number q such that k < q < 1. Then from a certain n 

onward, that is, when n > n , it is certain that -2±i < q or 
V | a n | < q, as the case may be, since from a certain term 
" x ' or of V | a„ | differ from k by less 



onwards the values of 



On 



than (q — k). The statement is then established by a reference 
to the results already proved. 

We stress the point that the four tests derived from the 
original criterion | a n | < cq n are not equivalent to one another 
or to the original, that is, that they cannot be derived from 
one another in both directions. We shall soon see from examples 
that if a series satisfies one of the conditions, it need not by any 
means satisfy all the others.* 

For completeness it may be pointed out that a series cer- 
tainly diverges if from a certain term onward 

| a n | > c 

for a properly chosen positive number c, or if from a certain term 
onward 



or if lira 



*n+l 



V I a„ | > 1, 
= k, or lira V | a n | = k, 



where k is a number greater than 1. For, as we immediately 
recognize, in such a series the terms cannot tend to zero as n 
increases; the series must therefore diverge. (In these circum- 
stances the series cannot even be conditionally convergent.) 

Our tests furnish sufficient conditions for the absolute con- 
vergence of a series; that is, when they are satisfied we can con- 
clude that the series converges absolutely. They are definitely 
not necessary conditions, however; that is, absolutely convergent 
series can be found which do not satisfy the conditions. 

* More exactly: if Ilia is fulfilled, then Ho is fulfilled; if III6, then 116; 
if Ilia, then III6; if Ila, then 116; and if any of the four is satisfied, then so 
is I. None of these statements can be reversed. 



3«o INFINITE SERIES 

For example, the knowledge that 



[Chap. 



lim 



*n+l 



= 1 or lim ■$/ | a„ \ = 1 



does not entitle us to make any statement about the convergence 
of the series. Such a series may converge or diverge. For 
example, the series 

1 



S 



for which lim V | a n \ = 1 and lim 



a n+l 



= 1, is divergent, 



as we saw on p. 368. On the other hand, we shall soon see that 

00 ] . 

the series S — , which satisfies the same relations, is con- 

n-lW 2 

vergent. 

As an example of the application of our tests we first consider the 
series 

q + 2q<> + 3q* + . . . + w? + . . . . 
For this series 

J™ V'KI = I S I • lim V» = | q \, 



lim 



*«+i 



. lim 

«— >« 



»+ 1 



1*1- 



That the series converges if | q | < 1 follows from the ratio test and from 
the root test also, even in the weaker form III. 
If, on the other hand, we consider the series 

1 + 2 2 + g" + 2? + . . . + q™ + 2g 2 "+i + . . . , 

we can no longer prove convergence by the ratio test when 1 g I q I < 1; 

for then -=^— = 2 | q | ^ 1. But the root test immediately gives us 

lim -y/ 1 a„ | = q\, and shows that the series converges provided 
that | q | < 1, which, of course, we could also have observed directly. 

3. Comparison with an Integral.* 

We now proceed to a discussion of convergence which is independent 
of the preceding. We shall cany it out for the particularly simple and 
important case of the series 

"1 11 

* In this connexion see also the appendix to Chap. VII (p. 361). 



VIII] 



CONVERGENCE TESTS 



38i 



where the general term a n is l/n% a being a positive number. In 
order to investigate the convergence or divergence of this series, we 
consider the graph of the function y = 1/a? 1 and mark off on the x-axis 

the integral abscissae as= 1, x—2 We first 

construct the rectangle of height l/n a over the interval 
» — 1 ^x :g ra of the a--axis (n. > 1), and compare it 
with the area of the region bounded by the same 
interval of the z-axis, the ordinates at the ends, and 
the curve y = l/cc° (this region is shown shaded in 
fig. 2). Secondly, we construct the rectangle of height 
l/n a lying above the interval n gign -f- 1, and 
similarly compare it with the area of the region lying 
above the same interval and below the curve (this 
region is cross-hatched in fig. 2). In the first case the 
area under the curve is ob- 
viously greater than the 
area of the rectangle; in the 
second case it is less than 
the area of the rectangle. In 
other words, 

J„ VP- »« Jn-lX* 




Fig. 2. — Comparison of a series with an integral 



as we may also prove directly from the integral itself (cf . Chap. II, § 7, p. 129). 
Writing down this inequality for n = 2, n = 3 n = m and summing, 

we obtain the following estimate * for the m-th partial sum a = 2 - : 






* +1 dx r m dr 



Jr" 1 
— dx tends to a finite limit or increases 
1 *" 
without limit according as a > 1 or a ^ 1. Consequently the monotonia 
sequence of numbers s m is bounded or increases beyond all bounds accord- 
ing as a > 1 or a S 1, and we thus have the following theorem: 

* From this relation for o - 1 it follows at once that the sequence of 
numbers 0,-1+2+- + ... + -- log nis bound ed below. Since from the 

inequality ~-^ < J — - l og (n + 1) - l og » we see that the sequence 
is monotonic decreasing, it must approach a limit 

lim C n - Urn (1 + 5 + 5 + . . . + i - logn) - 0. 

The number G, whose value is -5772 . . . , is called Eider's constant. In 
contrast to the other important special numbers of analysis, such as it and e 
no other expression with a simple law of formation has been found for Euler's 
constant. 



38a INFINITE SERIES [Chap. 

The aeries 

.^ 1 ^~F + ^ + r« + ••• 

is convergent — and, of course, absolutely convergent — if, and only if, a. > 1. 
The divergence of the harmonic series, which we previously proved 
in a different way, is an immediate consequence of this. In particular, 
we see that the series 

1 + 1 + 1 + 

I+ 1 +^+ 

13 ^ 2 3 3 3 ' 



converge. 

00 i 

The series 2 — , whose convergence we have just studied, frequently 

,,= 1 v a 

serve as comparison series in investigations of convergence. For example, 

00 c 
we see at once that for a > 1 the series S — converges absolutely if the 

absolute values | c„ | of the coefficients remain, less than, a fixed bound 
independent of v. 



Examples 
Find whether the series in Ex. 1-6 are convergent or not: 

2. I t 

1 V* 



CO 1 

3. S 



l Vv(v + 1) 
,te the error 

(_l)v + l 



— 1 "* 



1 



8. S 
— iv! 



4. 


00 

* S 


1 

2 (l0gv)«' 


a fixed. 


5. 


CO 

s 

r—2 


1 

(logv) Io K"' 




6. 


CO 

2 


V 




[ the series in Ex. 


7-10: 


9. 


CO 

s 

»— 1 


i 

v" 




10. 


CO 

^=1 


V 





11. Prove that 2 sin s I tc( v + -J converges. 

CO Q0 

12. Does S e~ v ' (that is, 1 + 2 S er v ') converge? 

co ! 

13.* Prove that 2 — converges when a > 1 and diverges when 

a ^ L ,-2v(logv)» 



VII1J CONVERGENCE TESTS 383 

« 1 

14.* Prove that S — - — ; converges when a > 1 and diverges 

when a £ 1. ,=3 v log v (log log v)- 

15. Prove that if u ( 3j (*' = 1, 2, 3, . . .) and S w t converges, then 

00 (=1 

S Uf* also converges. 
t"=-i 

OO 00 DO 

16. Show that if S a k * and S b k * both converge, then S a,Jb k also 
converges. *" =1 * =1 * =1 



17 


Prove that 












'+$-;+;+ 


1 

5 


-? + ! + .. 

6 7 


.+ X 

3n+ 1 










+ X - 2 +• 
3» + 2 3n + 3 


. . = log3 


18 


* Prove that if n 


is 


an arbitrary 
00 „ n 


integer greater 
log », 


than 1 


where 


a„" is denned as 


follows: 








— n 




1 if n is not a factor of «, 





3. Sequences and Series op Functions 

1. General Remarks. 

The terms of the infinite series hitherto considered have been 
constants; hence these series (when convergent) always repre- 
sented definite numbers. But both in theory and in applications 
tne series of outstanding importance are those in which the terras 
are functions of a variable, so that the sum of the series is also 
a function of the variable, as in the case of Taylor series. 

We shall therefore consider a series 

9iW + 9z( x ) + 9s(x) + • • • » 

in which all the functions g n (x) are functions denned in an interval 
a 5S x ^ b. The w-th partial sum of this series, 

9ii x ) + 9z( x ) + • - - + gJ?), 

we denote by f n (x). Then the sum f(x) of our series, where it 
exists, is simply the limit lim fjx). 



3»4 INFINITE SERIES [Chap. 

We may therefore regard the sum of an infinite series of func- 
tions as the limit of a sequence of functions f^x), f 2 {x), . . . , 
f„{x), .... Conversely, for any such sequence of functions 
fi( x )> fi( x )> ... we can form an equivalent series by putting 
?i(*) =/i(*) an d g n (x) =f n (x) —f n ^(x) for n > 1. When it 
is convenient, therefore, we can pass from the consideration of 
series to that of sequences and conversely. 

2. Limiting Processes with Functions and Curves. 

We shall now state exactly what we mean by saying that a 
function /(a;) is the limit of a sequence f x {x), f 2 (x), . .., f„(x), . . . 
in an interval a <^ x <^ b. The definition is as follows: the 
sequence f^x), f z (x), . . . converges in that interval to the limit 
function f(x), if at each point x of the interval the values f n (x) 
converge in the usual sense to the value f(x). In this case we 
shall write lim/„(a;) =f(x). According to Cauchy's test (cf. p. 40) 

n— >oo 

we can express the convergence of the sequence without 
necessarily knowing or stating the limit function f(x). For 
our sequence of functions will converge to a limit function if, 
and only if, at each point x in our interval and for every posi- 
tive number e the quantity \f„(x) —fjx) | is less than e, pro- 
vided that the numbers n and m are chosen large enough, that 
is, larger than a certain number N = N(e). This number N(e) 
usually depends on e and x and increases beyond all bounds as e 
tends to zero. 

We have frequently met with cases of limits of sequences of 
functions. We mention only the definition of the power x" for 
irrational values of a by the equation 

x a = lhna; r », 

where r v r 2 , . . . , r„, . . . is a sequence of rational numbers 
tending to a; or the equation 



= lim 
n 



00 \ n/ 



where the functions f n (x) on the right are polynomials of degree n. 

The graphical representation of functions by means of curves 

suggests that we can also speak of limits of sequences of curves, 

saying, for example, that the graphs of the above limit functions 



VIII] SEQUENCES AND SERIES OF FUNCTIONS 385 




C 1 x 

Fig- 3- — Limit curve and limit function 



a; a and e* are to be regarded as the limit curves of the graphs of 

the functions x r * and ( 1 + - 1 respectively. There is, however, 

a fine distinction between passages to the limit with functions 
and with curves. Until the middle of the nineteenth century 
this distinction was not sufficiently observed; only by having 
a clear idea of it can we avoid apparent paradoxes. We shalJ 
illustrate this point by an example. 

For this purpose we consider the 
functions 

/„(*) = *" (n=l,2,...) 

in the interval ^ x g 1. All these 
functions are continuous, and the 
limit function lim f n (x) = /(x) exists. 

n — y 00 

But this limit function is not con- 
tinuous. On the contrary, since 
for all values of n the value of the 
funotion/„(l) = 1, the limit 

/(1)=1; 
while, on the other hand, for ^ x < I, the limit f(x) = lim f„(x) = 0, 

n— >oo 

as we saw in Chap. I, § 5 (p. 33). The function f(x) is therefore a discon- 
tinuous function which at x = 1 has tho value 1 and for all other values 
of x in the interval has the value 0. 

This discontinuity becomes intelligible if we consider the graphs G 
of the functions y = f„(x). These (cf. fig. 16, p. 33) are continuous ourves" 
all of which pass through the origin and the point x = 1, y = 1, and which 
draw in closer and closer to the x-axis as n increases. The curves possess 
a limit curve G which is not discontinuous at all, but consists (cf. fig. 3) 
of the portion of the x-axis between x = and x = 1, and the portion of 
the line x = 1 between y = Q and y = 1. The curves therefore converge 
to a continuous limit curve with a vertical portion, while the functions 
converge to a discontinuous limit function. We thus recognize that this 
discontinuity of the limit function expresses itself by the occurrence in 
the limit curve of a portion perpendicular to the x-axis. Such a portion 
must involve a discontinuity in the limit function, and, in fact, such a 
portion is always present when the limit function is discontinuous. This 
limit curve is not the graph of the limit function, nor can any curve with 
a vertical portion be the graph of any single- valued function y = /(x); 
for corresponding to the value of x at which the vertical portion occurs 
the curve gives an infinite number of values of y and the function only 
one. Hence the limit of the graphs of the functions / n (x) is not the same 
as the graph of the limit f(x) of these functions. 

Corresponding statements, of course, hold for infinite series also. 



386 



INFINITE SERIES 



[Chap. 



4. Uniform and Non-uniform Convergence 

1. General Remarks and Examples. 

The distinction between the concept of the convergence of 
functions and that of the convergence of curves introduces a 
phenomenon which it is essential that the student should 
clearly recognize. This is the so-called non-wniform conver- 
gence of sequences or infinite series of functions. Since it is well 
known that beginners usually find difficulties here, we shall 
discuss the matter in some detail. 





/f'~^ 


^ ->y-flx)+t 




' is^~ 


^*Ai)-f(x) 


y-fnCcf J f\, 




t 
1 

1 



a b x 

Fig. 4. — To illustrate uniform convergence 

That a function f(x) is the limit of a sequence fi(x), fyx), . . . 
in an interval a 5£ x ^ b means only, by definition, that the 
usual limit relationship f(x) = lim/(a;) holds at each point x of the 

interval. From a naive point of view one might expect that the 
following fact would automatically follow from this concept of 
convergence: if we assign an arbitrary degree of aocnracy, say 

e ~ Taoo oi € ~ 77wV *^ ei1 * rom a cerfcam index N onward all 

the functions /„(a?) will lie between/fa) + e and f(x) — e for all 
values of x, so that their graphs y=f n (x) will lie entirely in 
the strip indicated in fig. 4. That is to say, for every positive e 
there is a corresponding number N = N (e), which, of course, 
will ordinarily increase beyond all bounds as c -*- 0, such that 
for » > N the difference \f(x) —f„{x) | < e, no matter where 
x is chosen in the interval. (If this condition is fulfilled, then 



VIII] UNIFORM CONVERGENCE 387 

\fn(x) —fmfo) I < 2e for all values of x, provided that n and m 
are both greater than N.) If the accuracy of the approximation 
can be made at least equal to a pre-assigned number e everywhere 
in the interval at the same time, that is, by everywhere choosing 
the same number N(e) independent of x, we say that the 
approximation is uniform. One is at first astonished to find that 
the naive assumption that convergence is necessarily uniform is 
entirely wrong; in other words, that convergence may very well 
be non-uniform. 

Ex. 1. Non-uniform convergence occurs in the case of the sequence 
of functions just considered, f n (x) = x"; in the interval Ogjz^l this 
sequence converges to the limit function f(x) = for g x < 1, /(l) = 1. 
Convergence occurs at every point in the interval; that is, if e is any posi- 
tive number, and if we select any definite fixed value x = 5, the 
inequality | 5" — /(?) | < e certainly holds if n is sufficiently large. Yet 
this approximation is not uniform. For, if we choose e = J, then 
no matter how large the number n is chosen, we can find a point 
x = y) 4= 1 at which | if — /(yj) | = rf > £; this is, in fact, true for 
all points x — tq where 1 > yj > ty\. It is therefore impossible to choose 
the number n so large that the difference between f(x) and f n {x) is less 
than \ throughout the whole interval. 

This behaviour becomes intelligible if we refer to the graphs of these 
functions (fig. 3, p. 385). We see that no matter how large a value of n we 
choose, for values of \ only a little less than 1 the value of the function 
/n(5) will be very near 1, and therefore cannot be a good approximation to 
/(£), which is 0. 

Similar behaviour is exhibited by the functions 

/„(*) = 



! + »*» 



in the neighbourhood of the points x = 1 and x = — 1; this can easily 
be established. (Compare also the discussion in Chap. I, § 8 (p. 52)). 
Ex. 2. In the two examples above the non-uniformity of the conver- 
gence is connected with the fact that the limit function is discontinuous. 
Yet it is also easy to construct a sequence of continuous functions 
which do converge to a continuous limit function, but not uniformly. 
We restrict our attention to the interval ^ x 2j| 1 and make the follow- 
ing definitions for » J> 2: 

f„(x) = xn a for ^ x ^ -, 
n 

/«(*) = (- - *) »" for - 5 x g ?, 
\» / n n 

f n (x) = for - ^ x g 1, 
n 



J88 



INFINITE SERIES 



[Chap. 



where to begin with we can choose any value for a, but must then 
keep this value of a. fixed for all terms of the sequence. Graphically 
our functions are represented by a roof-shaped figure made of two line 
segments lying over the interval ^ x ^ 2/»i of the x-axis, while from 
x — 2/n onwards the graph is the x-axis itself (cf. fig. 6). 

If a < 1, the altitude of the highest point of the graph, which has in 
general the value » a_1 , will tend to as n increases; the curves will then 
tend towards the x-axis, and the functions f n (x) will converge uniformly 
to the limit function f(x) = 0. 

If a = 1, the peak of the graph will have the height 1 for every value 
of n. If a. > 1, the height of the peak will increase beyond all bounds as 
n increases. 

But no matter ho-w a. is chosen, the sequence f^x), f 2 {x), . . . always 
tends to the limit function /(x) = 0. For, if x is positive, for all sufficiently 






n 



A 



Fig. 5. — To illustrate non-uniform convergence 

large values of n we have 2/ra < x, so that x is not under the roof-shaped 
part of the graph and / n (x) = 0; for x = all the functional values /„(«) 
are equal to 0, so that in either case lim /„(x) = 0. 

The convergence is certainly non-uniform, however, if a ^ 1; for it 
is plainly impossible to choose n so large that the expression |/(x) — /„(x) | 
= / n (x) is less than J everywhere in the interval. 

Ex. 3. Exactly similar behaviour is exhibited by the sequence of 
functions (cf. fig. 6) 

/ n (x) = xn"er«*, 

where, in contrast with the preceding case, each function of the sequence is 

represented by a single analytical expression. Here again the equation 

ft" 1 fn( x ) — holds for every positive value of x, since as n increases the 

n — >» 

function e~ nx tends to to a higher order than any power of l/» (of. Chap. 
Ill, § 9, p. 192). For x = 0, we have always /„(x) = 0, and thus 

f(x) = lim /„(x) = 



VIII] 



UNIFORM CONVERGENCE 



389 



for every value of a: in the interval O^igo, where a is an arbitrary 
positive number. But here again the convergence to the limit function 

is not uniform. For at the point x = - (where f n (x) has its maximum) 
we have 






and we thus recognize that if a 2: 1, the convergence is non-uniform; 
for every curve y = f„(x), no matter how large n is chosen, will contain 

points (namely, the point x = , which varies with n, and neighbouring 

* 1 

points) at which /„(*) - f{x) = f„(x) > —. 

Ze 




Fig. 6 

Ex. 4. The ooncepts of uniform and non-uniform convergence may, 
of course, be extended to infinite series. We say that a series 

gi(x) + 3i(x) + • • • 

is uniformly convergent, or not, according to the behaviour of its partial 
sums f„(x). A very simple example of a non-uniformly convergent series 
is given by 

x* iB* X* 

/(*) = *+__ + __+___ + ... . 
For * = every partial sum f n (x) = x* + . 



f (T+l^ hMthe 

value 0; therefore /(0) = 0. For x 4= the series is simply a geometric 

series with the positive ratio < 1; we can therefore sum it by the 

1 + 3? 

elementary rules and thus obtain for every i+0 the sum 

a~> 



1 - 1/(1 + **) 



= 1 + x\ 



The limit function f(x) is thus given everywhere except at x = by the 
expression f(x) — 1 + x\ while /(0) = 0; it therefore has a somewhat 
artificial-looking discontinuity at the origin. 



390 



INFINITE SERIES 



[Chap. 



Here again we have non-uniform convergence in every interval con- 
taining the origin. For the difierence f(x) — f n (x) = r n (x) is always for 
x = 0, while for all other values of x it is given by the expression 

r n( x ) = Tp-r — tt=zp as the reader may verify for himself. If we require 
(1 ~f- ar)™" -1 

this expression to be less than, say, J, then for each fixed value of x this 

can be attained by choosing n large enough. But we can find no value of 

n sufficiently large to ensure that r„(x) is everywhere less than J; for if 

we fix upon any value of n, no matter how large, we can make r n (x) greater 

than J by taking x near enough to 0. A uniform approximation to within 

J is therefore impossible. The matter becomes clear if we consider the 

approximating curves (cf. fig. 7). These curves, except near x == 0, lie 




nearer and nearer to the parabola y = 1 + x* as n increases; near x = 0, 
however, the curves send down a narrower and narrower extension to 
the origin, and as n increases this extension draws in closer and closer to 
a certain straight line, a portion of the y-axis, so that for limiting curve 
we have the parabola plus a linear extension reaching vertically down 
to the origin. 

As a further example of non-uniform convergence we mention the 

00 

series 2 g y (x), where g v (x) = x" — a;" -1 for v ^ 1, g e {x) = 1, defined in 

the interval OgaiSl. The partial sums of this series are the functions 
x" already considered in the first example (p. 387). 

2. A Test of Uniform Convergence. 

The preceding considerations show us that the uniform con- 
vergence of a sequence or series is a special property not possessed 



VIII] UNIFORM CONVERGENCE 39 1 

by all sequences and series. We shall now formulate the concept 
of uniform convergence again. The convergent series 

9ii*) + 9a( x ) + ; • • 

is said to be uniformly convergent in an interval if the sum f(x) 
can be approximated to within e (where e is an arbitrarily small 
positive number) by taking a number of terms which is suffi- 
ciently large and which is the same throughout the interval. 

We suppose first that the series g^x) + g 2 (x) + . . . converges 
at every point of a certain interval to a limit function f(x); by 
f n {x) we denote the »-th partial sum of the series, f n (x) = 
9i( x ) + • • • + 9dp)> and by Jt n (x) the remainder of the series 
after n terms, 

K(x)=f(x)-f n (x). 

The series g^x) + g 2 (x) + ... is said to be uniformly con- 
vergent in the interval if to every positive number e there corresponds 
a number N, dependent on e alone and not on x, such that for n > N 
the inequality | R n (x) | = | f (x) — f^x) | < e holds for all values 
of x in the interval. 

Expressed more pictorially, the partial sum f n (x) represents 
the sum f(x) to within an error of less than e everywhere in the 
interval at the same time, provided only that n is chosen large 
enough. By Cauchy's test we readily see that the series converges 
uniformly if, and only if, the difference |/ n (a:) —fjx) | can be 
made less than an arbitrary quantity e everywhere in the interval 
by choosing n and m larger than a number N independent of x. 
For, firstly, if the convergence is uniform we can make 
\f«{x) —f{x) | and \f m (x) — /(*) | both less than e/2 by choosing 
n and m greater than a number N independent of x, from which 
itfollowsthat |/„(x) -/„(») \<e; and secondly, if \f n (x)-fjx) |<e 
for all values of x whenever n and m are greater than N, then on 
choosing any fixed value of n > N and letting m increase beyond 
all bounds we have the relation 

!/.(*) -/(*) I = lim \f„(x) ~f m (x) | ^ e , 

for every value of x, so that the convergence is uniform. 

If we wish to speak of the uniform convergence of a sequence 
of functions we need make only trifling changes in the above 



392 INFINITE SERIES [Chap. 

definition; the sequence f^x), f 2 (x), . . . converges uniformly to 
f(x) in an interval if the difference |/(a;) —f n (x) | can be made 
less than « everywhere in the interval by choosing n greater 
than a number N independent of x. As above, a necessary and 
sufficient condition for the uniform convergence of the sequence 
is that | f n {x) —fjx) j < e for all values of x when n and m are 
both greater than a certain number N dependent on e but not 
on x. 

We shall soon see that it is just this condition of uniform 
convergence that makes infinite series and other limiting pro- 
cesses with functions into convenient and useful tools of analysis. 
Fortunately, in the limiting processes usually encountered in 
the calculus and its applications, non-uniform convergence is a 
sort of exceptional phenomenon which will scarcely trouble us 
in our present applications of analysis. 

In most cases the uniformity of convergence of a series is 
established by means of the following criterion: 

00 

If the terms of the series S g„(x) satisfy the condition | g„(x) | ^ a,,, 
where the numbers a„ are constants which form a convergent series 

00 00 

S a„, then the series 2 g„(x) converges uniformly (and, we may 

incidentally remark, absolutely). 
For we then have 

| lg v (x) | ^S | &Gr)| ^So„ 

v«=n v=n v*=n 

m 

and since by Cauchy's test the sum 2 a v can be made arbitrarily 

small by choosing n and m > n large enough, this exactly ex- 
presses the necessary and sufficient condition for uniform con- 
vergence. 

A first example is ofiered by the geometries series 1 -f- x -\- x* + . . . 
where x is restricted to the interval \x\ g q, q being any positive number 
less than 1. The terms of the series are then numerically less than or equal 
to the terms of the convergent geometric series Eg*. 

A further example is given by the " trigonometric series " 

frsinfo— Sj) c 8 sin(a;— S a ) c g sin(a!— 8 3 ) 



VIII] UNIFORM CONVERGENCE 393 

provided that | c n | < c, where c is a positive constant independent of n. 
For then we have 

,„(*) = "»»*"(»-«■) , so that , (x) 1 < c 

Hence the uniform and absolute convergence of the trigonometric series 

00 c 
follows from the convergence of the series 2 — • 

3. Continuity of the Sum of a Uniformly Convergent Series of 
Continuous Functions. 

As we have already hinted, the significance of the uniform 
convergence of an infinite series lies in the fact that a uniformly- 
convergent series in many respects behaves exactly like the sum 
of a finite number of functions. Thus, for example, the sum of a 
finite number of continuous functions is itself continuous, and 
correspondingly we have the following theorem: 

If a series of continuous terms converges uniformly in an in- 
terval, its sum is also a continuous function. 

The proof is quite simple. We subdivide the series 

f(x) = g x (x) + g 2 (x) + ... 

into the n-th partial sum f n (x) plus the remainder R n (x). As 
usual, f n (x) — g^x) + . . . + g„{x). If now any positive number 
e is assigned, we can in virtue of the uniform convergence choose 
the number n so large that the remainder is less than e/4 through- 
out the whole interval, and hence 

\R n (x+h)-R n (x)\<^ 

for every pair of numbers x and x -\- h in the interval. The par- 
tial 8um/„(a;) consists of the sum of a finite number of continuous 
functions and is therefore continuous; for each point x in the 
interval, therefore, we can choose a positive 8 so small that 

!/.(* + *)-/.(*)!<? 

provided j h | < 8 and the points x and x + A lie in the interval. 
It then follows that 

\f(x + h) -fix) I = \f n {x + A) -/.(as) + R n (x +h)- R n (x) I 
^ I /J* + h) -f n (x) I + I R n (x +h)- R„(x) I < e , 

which expresses the continuity of our function. 



394 INFINITE SERIES [Chap. 

The significance of this theorem becomes clear when we recall 
that the sums of non-uniformly convergent series of continuous 
functions are not necessarily continuous, as our previous examples 
show. From the preceding theorem we may conclude that if the 
sum of a convergent series of continuous functions has a point 
of discontinuity, then in every neighbourhood of this point the 
convergence is non-uniform. Hence every representation of dis- 
continuous functions by series of continuous functions is based 
on the use of non-uniformly convergent limiting processes. 

4. Integration of Uniformly Convergent Series. 

A sum of a finite number of continuous functions can be 
" integrated term by term "; that is, the integral of the sum 
can be found by integrating each term separately and adding 
the integrals. In the case of a convergent infinite series the same 
procedure is permissible, provided that the series converges 
uniformly in the interval of integration. 

00 

A series S g p (x) = f (x) which converges uniformly in an interval 

can be integrated term by term in that interval: or, more precisely, 
if a and x are two numbers in the interval of uniform convergence^ 

00 /.X 

the series 2 / g„(t)dt converges, and, in fact, converges uniformly 
with respect to x for each fixed value of a, its sum being equal to 

f(t)dt. 

To prove this we write as before 

f(x) = Xg v (x)=f n (x) + R n (x). 

We have assumed that the separate terms of the series are con- 
tinuous; hence by the previous sub-section the sum is also con- 
tinuous and therefore integrable. Now if e is any positive 
number, we can find a number N so large that for every n> N 
the inequality | R„(x) | < e holds for every value of a; in the 
interval. By the first mean value theorem of the integral calculus 
we have 



•'a 



| jf (/(*)-/.(*))& 



el, 



VIII] UNIFORM CONVERGENCE 395 

where I is the length of the interval of integration. Since the 
integration of the finite axwif n (x) can be performed term by term, 
this gives us 

/"/(«)&-£ fgJit)dt <el. 
But since el can be made as small as we please, this states that 
S f 9v (t)dt = lim S [ X gMdt= f f(t)dt, 

which was to be proved. 

If, instead of i nfinit e series, we wish to deal with sequences 
of funotions, our result can be expressed in the following way: 

If in an interval the sequence of functions f^x), f 2 (x), . . . 
tends uniformly to the limit function f(x), then 



£f(x)dx = lim f f„(x)dx 



for every pair of numbers a and b lying in the interval; in other 
words, we can then interchange the order of the operations of in- 
tegration and passing to the limit. 

This fact is far from being a triviality. It is true that from a naive 
point of view such as prevailed in the eighteenth century the inter- 
ohangeability of the two processes is hardly to be doubted; but a glance 
at the examples in No. 1 of this seotion (p. 387) shows us that in the case 
of non-uniform convergence the above equation might not hold. We 
need only consider Ex. 2 (p. 387), in which the integral of the limit function 
is 0, while the integral of the function f n (x) over the interval <: x ^ 1, 
that is to say, the area of the triangle in fig. 5, p. 388, has the value 



/ 

Jo 



.1 
f n (x) dx = »»-*, 
'o 



and when a. ^ 2 this does not tend to zero. Here we immediately see 
from the figure that the reason for the difference between / f(x)dx 

/*1 Jq 

f n {x) dx lies in the non-uniformity of the convergence. 
.. , - 
On the other hand, by considering values of a such that 1 ^ a < 2, 

we see that the equation lim / f„{x)dx= f f(x)dx can hold good 

although the convergence is non-uniform. As a further example, the series 

S g n (x), where g n {x) = x n — a:"-* f or n > 1 and ?0 (x) = 1, can be inte- 



396 INFINITE SERIES [Chap. 

grated term by term between the limits and 1, even though it does 
not converge uniformly. Thus while uniformity of convergence is a 
sufficient condition for term-by-term integrability, it is by no means a 
necessary condition. Neglect of this point may easily lead to misunder- 
standing. 

5. Differentiation of Infinite Series. 

The behaviour of uniformly convergent series or sequences 
with respect to differentiation is quite different from that with 
respect to integration. For example, the sequence of functions 

f n (x) = certainly converges uniformly to the limit func- 

n 

tion f(x) = 0, but the derivative f n '(x) = n cosw 2 ^ certainly 

does not converge everywhere to the derivative of the limit 

function f'{x) = 0, as we see by considering x = 0. In spite of 

the uniformity of the convergence, therefore, we cannot change 

the order of the processes of differentiation and passing to the 

limit. 

Corresponding statements of course hold for infinite series. 

For example, the series 

. 8^2% . sin3*x , 

is absolutely and uniformly convergent, for its terms are numeri- 
cally not greater than the terms of the convergent series 

T5 + S5 + ^ + • • • • K > however, we differentiate the series 
12 2 2 3 2 

term by term, we obtain the series 

cosas + 2 2 cos2*a; + 3* cos3*a; + . . . , 

which plainly does not converge everywhere; for example, it 
diverges at x = 0. 

The only useful criterion which assures us in special cases 
that term-by-term differentiation is permissible is given by the 
following theorem: 

If, on differentiating a convergent infinite series S G„(x) = F(x) 

term by term, we obtain a uniformly convergent series of continuous 

00 

terms S g„(x) = f(x), then the sum of this last series is equal to the 

v-0 



VIII] UNIFORM CONVERGENCE 397 

derivative of the sum of the first series. This theorem, therefore, 
expressly requires that after differentiating the series term by 
term we must still investigate whether the result of the differen- 
tiation is a uniformly convergent series or not. 

The proof of the theorem is almost trivial. For by the theorem 
in No. 4 (p. 394) we can integrate term by term the series ob- 
tained by differentiation. Recalling that gj(t) = G r '(t), we obtain 

f X f(t)dt = f (2 gjtf))dt = S fg v (t)Zt = S (6 v (x) - <?») 
= F(x) — F(a). 

This being true for every value of x in the interval of uniform 
convergence, it follows that 

/(*) = F(x), 

which was to be proved. 

Examples 

1. Show by comparison with a aeries of constant terms that the follow- 
ing series converge uniformly in the intervals stated: 



(a) x - x* + a? - x* + . . . (- J g x g \). 



(6) JVl - a* + JVl - «• + JVl - *• + . . . + 5= Vl^T^n + . . . 
(-lgigl). 2 

, . sina: sin2a; sinna: , 

( c >^r+-p- + --- + -^- + .... 

(d) e* + e 2 * -J- . . . + e"* + . . . (-2 g x g -1). 

2. Prove that lim/„(x) = 0, where /„(») = ** -Igi^i. 
Prove that the convergence is non-uniform. 1 + n x* 

3* (a) Find lim f n (x), where /.(*) = f ** -1 ^ x ^ 1. Prove 

that the convergence is non-uniform. Prove that nevertheless 

-1 T 



lim f f n (x)dx = f lim f n (x)dx. 



(6) Discuss the behaviour of the sequence given by f n (x) = ~ 



n*x* 



1 -r- n-x" 
with regard to convergence, uniform convergence, and term -by -term 
integrability. 

4.* Sketch the curves y = /„(*) = _, — 2 g x g 2, for n = 1, 

1 + X?" 

3, 10. Find lim f„(x). Prove that the convergence is non-uniform. 



398 INFINITE SERIES [Chap. 

X 

5. Show that 2 e~<*-">' converges uniformly in any fixed interval 

6. Show that in the interval ^ x g ie the following sequences con- 
verge, but not uniformly: 



(a) v'sinz. (d) [/(*)]» where f(x) = !^?, /(0) = 1. 

(6) (sinz)» * 

sin a; 
x 



i \ "/ ' " h sin x 

(c) yzsinz. (e) y^), where /(*) = , /(0) = 1. 



7. The sequence f n (x), n = 1, 2, . . . , is defined in the interval 
O^J^l by the equations 



(a) Prove that in the interval O^igl the sequence converges to 
a continuous limit. 

(&)* Prove that the convergence is uniform. 

8.* Let f (x) be continuous in the interval Ogi^i The sequence 
of functions f„(x) is defined by 






Prove that in any fixed interval O^iga the sequence converges uni- 
formly to 0. 

9. Sketch the curves x* n + y in = 1 for n = 1, 2, 4. To what limit do 
these curves tend as n -> oo ? 

10.* Let f n (x), n = 1, 2, . . . , be a sequence of functions with con- 
tinuous derivatives in the interval a :£ x Ss 6. Prove that if /„(») con- 
verges at each point of the interval and the inequality | f n '(x) \ < M (where 
M is a constant) is satisfied for all values of n and x, then the convergence 
is uniform. 



5. Power Series 

Among infinite series, power series occupy the chief place. 
By a power series we mean a series of the type 

00 

P(x) = c + <%x + C 2 X* + ... = £ c y x* 

*=.o 

(" power series in x "), or more generally 

00 

P(x) = c + c^x — a: ) + c 2 {x — x ) 2 + . . . = 2 c v (x — x ) r 

(" power series in (a; — x ) "), where x is a fixed number. If 
in the last series we introduce f = x — x as a new variable, 



VIII] POWER SERIES 399 

it becomes a power series 2 c v £° in the new variable £, and we 

v = 

can therefore confine our attention to power series of the more 

00 

special form S c v x" without any loss of generality. 
>-=o 
In Chap. VI (p. 320) we considered the approximate repre- 
sentation of functions by polynomials and were thus led to the 
expansion of functions in Taylor series, which are in fact power 
series. In this section we shall study power series in some- 
what greater detail, and shall obtain the expansions of the most 
important functions in series in simpler and more convenient 
ways than before. 

1. Convergence Properties of Power Series. 

There are power series which converge for no value of x, 
except of course for x = 0, e.g. the series 

x + 2 a a? + 3^ + . . . + n n x n + ... . 

For if x 4= 0, we can find an integer N such that 
I x I > 1/2V. Then all the terms n n x n for which n > N will be 
greater than 1 in absolute value, and, in fact, as n increases n n x n 
will increase beyond all bounds, so that the series fails to converge. 
On the other hand, there are series which converge for every 
value of x; for example, the power series for the exponential 
function, 

e»= l + x + - + -+ .... 
2! 3! ' 

whose convergence for every value of x follows at once from the 
ratio test (Criterion Ilia, p. 378). The (n + l)-th term divided 
by the w-th term gives x/n, and, whatever number x is chosen, 
this ratio tends to zero as n increases. 

The behaviour of power series with regard to convergence is 
expressed in the following fundamental theorem: 

If a power series in x converges for a value x = f , it converges 
absolutely for every value x such that | x | < | £ \, and the convergence 
is uniform in every interval \ x | <S -q, where 7) is any positive 
number less than j £ |. Here r) may He as near | £ | as we please. 

00 

The proof is simple. If the series Sc„f converges, its terms 
tend to as n increases. From this follows the weaker 



4oo INFINITE SERIES [Chap. 

statement that the terms all lie below a bound M independent 
of v, that is, | c v g | < M. If now q is any number such that 
< q < 1, and if we restrict x to the interval | x | :S q | £ |, 
then | cX | ^ | c„£" | q" < Mq\ In this interval, therefore, the 

00 

terms of our series £ c v x" are smaller in absolute value than the 

o 
terms of the convergent geometric series ZMg". Hence from the 
theorem on p. 392 the absolute and uniform convergence of the 
series in the interval —q\ g\^,xi^q\ g\ follows. 

If a power series does not converge everywhere, that is, if 
there is a value x = g for which it diverges, it must diverge for 
every value of x such that | x | > | g |. For if it were convergent 
for such a value of x, by the theorem above it would have to 
converge for the numerically smaller value g. 

From this we recognize that a power series which converges 
for at least one value of x other than and which diverges for 
at least one value of x has an interval of convergence; that is, 
a definite positive number p exists such that for | x | > p the 
series diverges and for | x \ < p the series converges. For 
| x | = p no general statement can be made. The limiting 
cases, that in which the series converges only for x = and 
that in which it converges everywhere, are expressed sym- 
bolically by writing p — and p = oo respectively.* 

For example, for the geometric series 1 + x + 3? + . . . we have 
p = 1; at the end-points of the interval of convergence the series diverges. 
Similarly, for the series for the inverse tangent (p. 319), 

arc tana; = x — x 3 /3 + xfi/S h • • • > 

we have p = 1, and at both the end-points x = ±1 of the interval of 
convergence the series converges, as we recognize at once from Leibnitz's 
test (p. 370). 

* It is possible to find this interval of convergence directly from the co- 
efficients Cy of the series. If the limit lira «V \c n \ exists, then 

n— >•« v 

_ 1 

P limV/lcf 
»— >» 

In general p U given by the formula 



lim $ |c„| 



where Em is the symbol for the upper limit, as defined in the appendix to 
Chap. I (p. 62). 



VIII] POWER SERIES 401 

From the uniform convergence we derive the important fact 
that within its interval of convergence (if such an interval exists) 
the power series represents a continuous function. 

2. Integration and Differentiation of Power Series. 

On account of the uniformity of convergence it is always 
permissible to integrate a power series 

00 
f{x) = Sc/ 

■-=0 

term by term over any closed interval lying entirely within the 
interval of convergence. We thus obtain the function 

F(x) = c + Z, 4r^ 
for which F\x)=f{x). 

Further, since 



J, I c„ I for all values of v, the series 
v+1 

obtained by integration converges more rapidly than the original 
series. 

We can also differentiate a power series term by term within its 
interval of convergence, thus obtaining the equation 

f'(x) = 2 vc v x-~ l - 

In order to prove this statement we need only show that the 
series on the right converges uniformly if a; is restricted to an 
interval lying entirely within the interval of convergence. Sup- 
pose then that f is a number, lying as close to p as we please, 

for which 2 c r £" converges; then, as we have seen before, the 

numbers \c y ^\ all lie below a bound M independent of v, so that 

M 
I c v ^~ l I < j — i = N. Now let q be any number such that 

< q < 1; if we restrict x to the interval | x | 5S q | £ | , the terms 
of the series under discussion are not greater than those of the 

series £ | vc v q"~ 1 £*~ 1 \, and therefore less than those of the 
•-=.1 

00 

14 ( It 7981 



402 INFINITE SERIES [Chap. 

series 2 NvqT 1 . But in this last series the ratio of the (n + l)-th 

term to the n-th term is — — — q, which tends to q as w increases. 

n 

Since < q < 1, it follows (criterion Ilia, p. 378) that this series 
converges. Hence the series obtained by differentiation con- 
verges uniformly, and by the theorem at the end of last section 
(p. 396) represents the derivative f'(x) of the function f(x), 
which proves our statement. 

If we apply this result again to the power series 

00 

f'(x) = 2 vc v af~\ 

we find on differentiating term by term that 
/"(x) = Sv(v- l)c„x"- 2 , 

*=2 

and, continuing the process, we arrive at the theorem: Every 
function represented by a power series can be differentiated as 
often as we please within the interval of convergence, and the differen- 
tiation can be performed term by term.* 

3. Operations with Power Series. 

The preceding theorems on the behaviour of power series 
are our justification for operating in the same way with power 
series as with polynomials. It is obvious that two power 
series can be added or subtracted by adding or subtracting 
the corresponding coefficients (see p. 376). It is also clear that 
a power series, like any other convergent series, can be multi- 
plied by a constant factor by multiplying each term by that 
factor. On the other hand, the multiplication and division of 
two power series requires somewhat more detailed study, for 

* As an explicit expression for the fc-th derivative we obtain 
f<*>(x) -£■>(»- 1) ... (v - i + l)^"-*, 



y-t 

or in a slightly different form, 



4! 
These two formulas are frequently useful. 



£©—-£(* ;>"«-■ 



VIII] POWER SERIES 4°3 

which we refer the reader to the appendix (p. 416). Here we 
merely mention without proof that two power series 

00 

f{x) = Io/ 

»- 

00 

and g(x) = Tib y 3f 

K-0 

can be multiplied together like polynomials. To be specific, we 
have the following theorem: throughout the common part of 
the intervals of convergence of these two series their product is 

00 

given by the convergent power series 2 c y x", where the coefficients 

»— o 
c„ are given by the formulae 

c = ct b , 

<H. = a o°i + <hK> 

C a = a b 2 + <hW + a 2 b , 



c« = «o*» + °i&«-i + • • • + «n*0» 
(For the proof see the appendix, § 1, p. 416.) 

4. Theorem of Uniqueness for Power Series. 

In the theory of power series the following fact is of impor- 

00 00 

tance: if two power series So/ and Si,/ both converge in an 

v=0 >-=o 

interval which contains the point x = in its interior, and if in 
that interval the two series represent the same function f{x), 
then they are identical, that is, the equation o„ = 6„ is true for 
every value of n. In other words: 

A function f(x) can be represented by a power series in x in 
only one way, if at all. 

Briefly, the representation of a function by a power series 
is " unique ". 

To prove this we need only notice that the difference of the 

00 

two power series, that is, the power series <j>(x) = ~Lc v x" with 
coefficients c,= a„ — 6„, represents the function 
<j>(x)=f(x)-f(x) = 



404 INFINITE SERIES [Chap. 

in the interval; that is, this last power series converges to the 
limit everywhere in the interval. For x = 0, in particular, the 
sum of the series must be 0; that is, c = 0, so that a = 6 . 
We now differentiate the series in the interior of the interval, 

00 

obtaining (f>'(x) = S vc v x v ~ x . But <f>'(x) is also throughout 

i—i 
the interval; hence for x = 0, in particular, we have c x = 0, 
or %= b v Continuing this process of differentiating and then 
putting x = 0, we find successively that all the coefficients c„ 
are equal to zero, which proves the theorem. 

We see, in addition, that we can draw the following con- 
clusion from the above discussion: if we take the v-th derivative 
of a series /(a;) = Ea.X and then put x = 0, we at once obtain 

a, = l/e)(0), 

that is: 

Every power series which converges for points other than x = 
is the Taylor series of the function which it represents. 

The uniqueness of the expansion is here expressed by the 
fact that the coefficients are uniquely determined by the function 
itself. 



6. Expansion op Given Functions in Power Series. 
Method op Undetermined Coefficients. Examples 

Within its interval of convergence every power series repre- 
sents a continuous function with continuous derivatives of all 
orders. We shall now discuss the converse problem of the expan- 
sion of a given function in a power series. In theory we can always 
do this by means of Taylor's theorem; in practice we often meet 
with difficulties in the actual calculation of the ra-th derivative 
and in the estimation of the remainder. But we can often reach 
our goal more simply by making use of the following device. 

CO 

We first write down the statement f(x) — 2 c y af, where the 

coefficients c„ are unknown to begin with. Then by some known 
property of the function f(x) we determine the coefficients, and 
then prove the convergence of the series. The series represents 
a function, and it only remains to prove that this function is 



VIII] EXPANSION IN POWER SERIES 405 

identical with f(x). Because of the uniqueness of the expansion 
in power series we know that no other series than the one just 
found can be the required expansion. We shall now consider 
some examples of this method. Actually, we have already 
obtained the series for arc tana; and log(l + a;) by a method 
which forms part of the range of ideas of the present chapter. 
For we simply integrated term by term the series for the 
derivatives of these functions, which we knew to be geometric 
series. 

1. The Exponential Function. 

Our problem is to find a function /(*) for which f'(x) — f(x) and 
/(0) =1. If we write down the series with undetermined coefficients 

f(x) = c + c 1 x + c&?+ ... , 

and differentiate it, we obtain 

J'(x) = d + 2CaX + 3c,,s> + . . . ; 

Since by hypothesis these two power series must be identical, we have the 
equation 

"Cfl = c «-i> 

true for all values of n ^ 1. If we observe that because of the relation 
f(0) = 1 the coefficient c must have the value 1, we can calculate all the 
coefficients successively, and obtain the power series 

m=1 + Y< + i + i + '— 

As we easily see by the ratio test, this series converges for all values of x 
and therefore represents a function for which the relations f'(x) = f(x), 
/(0) = 1 are actually fulfilled. (Here we intentionally avoid making any 
use of what we have previously learned about the expansion of the ex- 
ponential function). 

Now the function e" certainly possesses these properties; we readily 
deduce that the function f(x) is identical with e*. For if we form the 
quotient <p{x) = f{x)jei" and differentiate we have 



^■ ^-/^ ■t 



The function <p(x) is therefore a constant, and since it has the value 1 for 
x = 0, it must be identically equal to 1, thus proving that our power 
series and the exponential function are identical (cf. the analogous dis- 
cussion on p. 178). 



4°* INFINITE SERIES [Cha> 

2. The Binomial Series. 

We can now return to the binomial series (Chap. VI, § 3, p. 329), this 
time making use of the method of undetermined coefficients. We wish 
to expand the function/(a;) = (1 + a:)* in a power series, and therefore write 

f(x) = (1 + *)«• = Co + c x x + c^ 2 + . . . , 

the coefficients c„ being undetermined. We now notice that our function 
obviously satisfies the relation 

(1 + x)f'(x) = af(x) = S a.c„x'. 

On the other hand, if we differentiate the series for f(x) term by term and 
multiply by (1 + x), we obtain 

(1 + x)f'(x) = c, -f (2c 2 + cjx + (3c s + 2c 2 )*2 + . . . ; 

and since these two power series for (1 + x)f'{x) must be identical, 

o^o — 6 i» «<h = 2cj + Cn ac a = 3c« + 2c 2 

Now it is certain that c = 1, since our series must have the value 1 
for x = 0, and so we obtain in succession the expressions 

r - „ , - (a- 1 )* ,. _ (a-2)(a-l)q 

cj — a, c 2 , c 4 — , ... i 

for the coefficients, and in general, as is easily established, we have 



c» 



(a- v + 



!)(«- v+2)...(a-l)a = /a\ 
v(v— 1)...2.1 W" 



00 M 
Substituting these values for the coefficients, we have the series S I Ja;'j 

y—0 vv/ 

we have yet to investigate the convergence of this series and to show that 

it actually represents (1 + x) a . 

By the ratio test we find that when a is not a positive integer, the 

series converges if | x \ < 1 and diverges if | x | > 1; for then the ratio 

a — Ti+1 

of the (n -f- l)-th term to the m-th term is x, and the absolute 

n 

value of this expression tends to | x | as n increases beyond all bounds.* 

Hence, if | x | < 1 our series represents a function f(x) which satisfies the 

condition (1 + x)f'(x) = ocf(x), as follows from the method of forming the 

* Here we state, without proof, the exact conditions under which this series 
converges. If the index a is an integer ^0, the series terminates and is there- 
fore valid for all values of x (becoming the ordinary binomial theorem). For all 
other values of a the series is absolutely convergent for | x \ < 1 and divergent 
for | a: | > 1. For x — + 1 the series converges absolutely if a > 0, converges 
conditionally if - 1 < a < 0, and diverges 3 a ^ — 1. Finally, at X — - 1 
the series is absolutely convergent if a > 0, divergent if a < 0. 



VIII] EXPANSION IN POWER SERIES 4°7 

coefficients. Moreover, /(0) = 1. But these two conditions ensure that 
the function J(x) is identical with (1 + x) a . For on putting 

9(*)« /<*)/(! + ■)■ 
we find that 

9 '(x) = (1 + xYi ' (x) ~ g(1 + x r~ l W = 0; 
(1 + a;) 2 " 

<f(x) is therefore a constant, and, in fact, is always equal to 1, since <p(0) = 1. 
We have therefore proved that when | x \ < 1 



(! + *)« = 2 (")*", 



which is the binomial series. 

Here we quote the following special cases of the binomial series: the 
geometric series 

= (1 + *)-i=l — x + x* — x* + x*— + ... 



1+x 



the series 

1 



(1 + *) 2 



. 2 (-iy x -, 

v=0 



= (1 + a:)- 2 = 1 — 2x + 3x* — 4ic" + — . , 



S (-l)"(v+l)x", 

v=0 



which may also be obtained from the geometric series by differentiation; 
and the series 

2.4.6.8 + ■••• 
1 .»(l + a .j-*»i_U+LL- 8 -«i--i^*ai 



V(l + x) 22.4 2.4.6 

, 1-3-5.7 

+ 2T4T6^* + "-' 

the first two or three terms of which form useful approximations. 

3. The Series for arc sin;*;. 

This series can be obtained very easily by expanding the expression 
l/v'(l — t a ) according to the binomial series, 



408 INFINITE SERIES [Chap. 

This series converges if | t | :£ 1, and so converges uniformly if | t | ^ q < 1. 
On integrating term by term between and x, we obtain 

, lx* , 1.31 s . 

arc smx = x + A + . . • ; 

2 3 2.45 

by the ratio test we find that this converges if | x \ < 1, and diverges if 
|*| >1. 

The deduction of this series from Taylor's theorem would be decidedly 
less convenient, owing to the difficulty of estimating the remainder. 

4. The Series for ar sinn* = log {x -j- -y^l + x 2 )}. 

We obtain this expansion by a similar method. Using the binomial 
theorem we write down the series for the derivative of ar sinhx, 

1 1 2 1.3 , 1.3.5 , 



V(l + * 2 ) 2 2.4 2.4.6 

and then integrate term by term. We thus obtain the expansion 

1 x 3 , 1 . 3 x 5 

ar suini = x — + 1- . . . , 

2 3 2.45 

whose interval of convergence is — 1 ^ x ^ 1. 

5. Example of Multiplication of Series. 
The expansion of the function 

log(l + * ) 

1 + x 

is a simple example of the application of the rule for the multiplication of 
power series. We have only to multiply the logarithmic series 

, „ . , 3? x 3 x* 

l0g(l + X)=X— ~ + j—j+ — ... 

by the geometric series 

1 = 1 — x + x* — 3? + x*— + ... ; 

1 + X 

as the reader may verify for himself, we obtain the remarkable expansion 

^— (>+5)-+0+j+J)* 
-(>+H + jW-- 

for j x | < 1. 



VIII] EXPANSION IN POWER SERIES 409 

6. Example of Term-by-Term Integration (Elliptic Integral). 
In previous applications we have met with the elliptio integral 

J V(l - k* sin 2 <p) 

(the period of oscillation of a pendulum (p. 302) ). In order to evaluate the 
integral we can first expand the integrand by the binomial theorem, 
thus obtaining 

1 1 + -& 2 sin 2 ? + — jfc 4 sin 4 ? 



V(l-fc 2 sin 2 9) 2 r 2.4 

. 1.3.5... . „ 
+ -— — -i 8 sm 6 <p+... i 
2.4.6 

Since k 2 sin 2 9 is never greater than k % this series converges uniformly for 
all values of <p, and we may integrate term by term: 

' ?1 =/ d<p + -k* sin*? dtp 

V(l- ifc a sin 2 <p) J r 2 J * 

, 1.3,, W 2 . , . , 

+ e 4 / sin 4 <p <J<p + . . . . 

2.4 J 

The integrals occurring here have already been calculated (cf. Chap. IV, 
§ 4, p. 223). If we substitute their values we have 

For further examples on the theory of series we refer the reader to 
the appendix (p. 415). 

Examples 

Determine the intervals of convergence of the series S a n x n , where 
a„ is given by the formulas in Ex. 1-20: n_1 

J 15. (-01 - l) n . 

16. W 
(2n)l 

._ »+ Vn 



1. 


1 

n 


2. 


n. 


3. 


1 

Vn 


4. 


Vn. 


5. 


1 

»T 2 ' 


6. 


n 


7 


1 




a + n 




I4» 



8. 


an -f- 6 


9 


1 




log(n + 1) 


10 


1 




log log lOn 


11. 


1 

$n' 


12. 


a n . 


13. 


a Vn . 


14. 


a l °e". 





n 2 — n 




18. 


1 

1 + a n 




19. 
20. 


Vn 
1 


_l)n 
n 



(■798) 



4io INFINITE SERIES [Chap. 

Expand the functions in Ex. 21-26 in power series: 
21. a x . 24. cos 2 x. 

•"• -^ • 25. sin's. 

23. sin 2 *. 26. arc sins". 

27. Using the binomial series, calculate V2 to four decimal places. 

28. Obtain approximations in series for the following integrals by 
expanding the integrand in a power series and integrating: 

(a) f lsi ? x dx. (c) /• 1 l°g(l + *) fa . 

Jo x J X 



(b) 



J ft dx , r lQ dx 

I Vd - *•)• w J s V(i + x*) 



29. By multiplication of power series obtain the expansions of the 
following up to the terms in a 4 : 

i„\ .js „,•_ ~ / v arc sin x 

(a) er smx. (c) 



Vl-a; 
(6) Dogd + x)?. . 

(a) sin 2 a;. 

30.* By multiplication of power series prove that 

(a) e*e* = e»"-». (6) sin 2x = 2 sin x cos a. 

31. If the interval of convergence of the power series Sa B i" is | x | < p, 
and that of 'Zb n x n is | x \ < p', where p < p', what is the interval of con- 
vergence of S(a„ + &„):*:"? 

32. Using the method of undetermined coefficients, find the function 
f(x) which satisfies the following conditions: 

(o)/(0)=3; (&) /'(*) = /(*) + *. 



7. Power Series with Complex Terms 

1. Introduction of Complex Terms into Power Series. 

The similarity between certain power series representing 
functions which are apparently unrelated led Euler to set 
up a purely formal connexion between them, found by 
giving complex values, in particular, pure imaginary values, 
to the variable x. We shall first do this formally, unhindered 
by questions of rigour, and shall investigate the results of the 
process. 

The first striking relation of this sort is obtained if we replace 



VIII] COMPLEX POWER SERIES 4" 

the quantity x in the series for e* by a pure imaginary ij>, where 
(f> is a real number. If we recall the fundamental equation 
for the imaginary unit i, that is, i 2 = — 1, from which it follows 
that i s = — i, i* = 1, i 5 = i, . . . , then on separating the real 
and the imaginary terms of the series, we obtain 

or, in another form, 

e»* = cos^ -)- i sin^. 

This is the well-known and important " Euler's formula "; 
as yet it is purely formal. It is consistent with De Moivre's 
theorem (p. 74), which is expressed by the equation 

(cos<£ -\- 1 sin<£)(cos^ + * sin^r) = cos(<£ + t[i) + i sin.(<f> -\- ifi). 

In virtue of Euler's formula this equation merely states that 
the relation 

C" . e v = e*+ v 

continues to hold for pure imaginary values x = i(f>, y^itfi. 

If we replace the variable x in the power series for cos a; by 
the pure imaginary ix we at once obtain the series for cosh a;; 
this relation can be expressed by the equation 

cosh x = cosmj. 

In the same way we obtain 

sinha;= - sinia;. 

Since Euler's formula also gives e^'*= cos^ — % sin<£, 

we arrive at the exponential expressions for the trigonometric 

functions, 

e ix — e~ ix e ix 4- e~ ix 

sins= — , cosa;=- — ! . 

2t 2 

These are exactly analogous to the exponential expressions 
for the hyperbolic functions and are, in fact, transformed into 

them by the relations coshx = cosia;, sinhz = T sinix. 

i 



412 INFINITE SERIES [Chap. 

Corresponding formal relations can, of course, be obtained 
for the functions tanas, tanhx, cot a;, cotha;, which are connected 

by the equations tanha; = - tana;, cotha; = icotix. 

Finally, similar relations can also be found for the inverse 
trigonometric and hyperbolic functions. For example, from 

« = tana; = = 

u »(«*» + «-*■) i(e**+l) 

we immediately find that 

1 — iy 

If we take the logarithms of both sides of this equation and then 

write x instead of y and arc tana; instead of x, we obtain the 

equation 

1 , 1 + ix 

arc tana; = — log -, 

%, 6 1 — vx 

which expresses a remarkable connexion between the inverse 
tangent and the logarithm. If in the known power series for 

_ log ' - (p. 318) we replace x by ix, we actually obtain 
2 1 — x 

the power series for arc tana;, 

1 .. . (ix) 3 . (ix) 6 . . 

arc tanx = - (ix + ^-~~ -f ^— '— + . . . ) 
i 3 5 

x 3 . X s , 

The above relations are as yet of a purely formal character, 
and naturally call for a more exact statement as to the meaning 
they are intended to convey. In the next sub-section we shall 
indicate how this can be given with the help of function theory. 

For later use, however, we shall only need Euler's formula 
e*'* = cos <j> + i sin <f> and, this being so, we can avoid a 
thorough analysis. We need only regard the symbol e** as a 
formal abbreviation for the right-hand side cos<£ + *sin<£, in 
which case De Moivre's formula e** . e 1 '* = e , ' M,+ ' w appears 
merely as a consequence of the elementary addition theorems of 
trigonometry. From this formal point of view, in order to make 



VIII] COMPLEX POWER SERIES 413 

the relation c* . e v = e* +v remain valid for any complex 
arguments, we set up the further definition 
e* = e* (cos 17 + i sirnj), 
where x = f + i-q (f, 17 being real). 

2. A Glance at the General Theory of Functions of a Complex 
Variable. 

Although the purely formal point of view indicated above is 
in itself free from objection, it is still desirable to recognize in 
the above formulae something more than a mere formal connexion. 
To follow out this aim leads us into the general theory of 
functions, as (for the sake of brevity) we call the general theory 
of the so-called analytic functions of a complex variable. In this 
we may use as our starting-point a general discussion of the 
theory of power series with complex variables and complex 
coefficients. The construction of such a theory of power series 
offers no difficulty once we define the concept of limit in the 
domain of complex numbers; in fact, it follows the theory of 
real power series almost exactly. But as we shall not make any 
use of these matters in what follows we shall content ourselves 
here by stating certain facts, omitting the proofs. It is found 
that the following generalization of the theorem of § 5, No. 1 
(p. 400), holds for complex power series: 

If a power series converges for any complex value x — £ what- 
ever, then it converges absolutely for every value x for which 
I x I < I 1 1; if it diverges for a value x = £, then it diverges for 
every value xfor which | x | > | £ |. A power series which does not 
converge everywhere, but does converge for some other point in addi- 
tion to x = 0, possesses a circle of convergence, that is, there exists 
a number p > such that the series converges absolutely for | x | < p 
and diverges for | x | > p. 

Having once established the concept of functions of a com- 
plex variable represented by power series, and having de- 
veloped the rules for operating with such functions, we can 
think of the functions e*, sina;, cosa;, arc tana;, &c., of the complex 
variable x as simply defined by the power series which represent 
them for real values of x. Then all the above formal relationships 
reduce to trivialities. 

We shall merely indicate by two examples how this intro- 
duction of complex variables helps us to understand the elemen- 



4H INFINITE SERIES [Chap. 

tary functions. The geometric series for 1/(1 -\- x 2 ) ceases to 
converge when x leaves the interval — 1 ^ x ^ 1, and so does 
the series for arc tana;, although there are no peculiarities in 
the behaviour of these functions at the ends of the interval of 
convergence; in fact, they and all their derivatives are con- 
tinuous for all real values of x. On the other hand, we can readily 
understand that the series for 1/(1 — as 2 ) and log(l — x) cease 
to converge as x passes through the value 1, since they become 
infinite there. But this divergence of the series for the inverse 

oo 

tangent and the series 2 (— l)"a^" for | x | > 1 immediately 

i/=0 

becomes clear if we consider complex values of x also. For we 
find that when x =i the sum-functions become infinite and so 
cannot be represented by a convergent series. Hence by our 
theorem about the circle of convergence the series must diverge 
for all values of x such that | x | > | i |; in particular, for real 
values of x the series diverge outside the interval — 1 ^ x jS 1. 

Another example is given us by the function f(x) = e~ 1/xS for 
x 4= 0,/(0) = (see pp. 196, 336), which, in spite of its apparently 
regular behaviour, cannot be expanded in a Taylor series. As 
a matter of fact, this function ceases to be continuous if we take 
pure imaginary values of x — i£ into account. The function then 
takes the form e ll( ' and increases beyond all bounds as $ -> 0. 
It is therefore clear that no power series in x can represent this 
function for all complex values of a: in a neighbourhood of the 
origin, no matter how small a neighbourhood we choose. 

These remarks on the theory of functions and power series 
of a complex variable must suffice for us here. 



VIII] MULTIPLICATION OF SERIES 4*5 

Appendix to Chapter VIII 

1. Multiplication and Division of Sebies 
1. Multiplication of Absolutely Convergent Secies. 

Let i = 2o„ B=S6 F 

be two absolutely convergent series. Together with these we 
consider the corresponding series of absolute values 

I = S|a„| and B = Jl\b r \. 
We further put 

A n = Za„ B„ = S&„, I„ = SK|, B n = i\b y \ 

V—0 V=0 V=0 F— 

and c„ = a b n + a 1 b n _ 1 -f . . . + a n b . 

00 

We assert that the series S c„ is absolutely convergent, and that 
its sum is equal to AB. " =0 

To prove this, we write down the series 

«(A) + <*A + °J>i + «A + °2*0 + °A 

-f" «A + «A + a oK + • • • + « A + <* A 
+ . . . + aj>n + ... + <hf>n + %?>„ + • • • » 

the w 2 -th partial sum of which is A„B n , and we assert that it con- 
verges absolutely. For the partial sums of the corresponding 
series with absolute values increase monotonically; the n 2 -th 
partial sum is equal to A n S n , which is less than AS (and which 
tends to AB). The series with absolute values therefore con- 
verges, and the series written down above converges absolutely. 
The sum of the series is obviously AB, since its n?-th partial sum 
is A„B n , which tends to AB as n -*■ oo. We now interchange 
the order of the terms, which is permissible for absolutely con- 
vergent series, and bracket successive terms together. In a 



4i6 INFINITE SERIES [Chap. 

convergent series we may bracket successive terms together in as 
many places as we desire without disturbing the convergence or 
altering the sum of the series, for if we bracket together, say, 
all the terms (a n+1 + a B+2 -f- . . . + a m ), then when we form the 
partial sums we shall omit those partial sums that originally fell 
between s„ and s m , which does not affect the convergence or 
change the value of the limit. Also, if the series was absolutely 
convergent before the brackets were inserted, it remains absol- 
utely convergent. Since the series 

00 

2 c v = (a b ) + (<*„&! + ajbo) + (a b 2 + a x \ + a 2 b ) + ... 

i/=0 

is formed in this way from the series written down above, the 
required proof is complete. 

2. Multiplication and Division of Power Series. 

The principal use of our theorem is found in the theory of 
power series. The following assertion is an immediate con- 
sequence of it: the product of the two power series 

00 00 

2 a v x v and 2 b„x v 

v=0 i/=0 

is represented in the interval of convergence common to the two 

CO 

power series by a third power series 2 c„x", whose coefficients are 
given by "~° 

c ^= a oK + <hK-i + • • • + aj> . 

As for the division of power series, we can likewise represent 
the quotient of the two power series above by a power 

00 

series 2 q v x", provided b , the constant term in the denominator, 

»— o 
does not vanish. (In the latter case such a representation is in 
general impossible; for it could not converge at x = on account 
of the vanishing of the denominator, while on the other hand 
every power series must converge at x = 0.) The coefficients 
of the power series 

00 

»— o 



VIII] MULTIPLICATION OF SERIES 417 

can be calculated by remembering that 2 q v x* . 2 b r x* = 2 a„x r , 

bo that the following equations must be true: 

a o = ?(&)> 

°i = Vo b i + ?i & <» 

a 2 = Voh + qfo + g- a & , 



°v = %K + ?A-i + • • - + ?A- 

From the first of these equations (ft, is readily found, from the 
second we find the value q x , from the third (by using the values 
of q and j x ) we find the value q 2 , &c. In order to give strict justi- 
fication for the expression of the quotient of two power series 

by the third power series we have still to investigate the con- 

00 
vergence of the formally-calculated power series 2 q v x". We 

»-o * 
shall pass over this general investigation, of whose result we 
shall make no further use, and shall content ourselves with the 
statement that the series for the quotient does actually converge, 
provided x remains within a sufficiently small interval, in which 
the denominator does not vanish and both numerator and 
denominator are convergent series. 

2. Infinite Series and Improper Integrals 

The infinite series and the concepts developed in connexion 
with them have simple applications and analogies in the theory 
of improper integrals (cf. Chap. IV, § 8, p. 249). Here we confine 
ourselves to the case of a convergent integral with an infinite 

interval of integration, say an integral of the form f f(x) Ax. 

If we divide up the interval of integration by a sequence of 
numbers x = 0, a^, . . . tending monotonically to + °o, we can 
write the improper integral in the form 

f o f{x)dx=a 1 + a 2 + .... 

where each term of our infinite series is an integral; 

f{x) dx, <%=) f(x)dx,..., 



4i8 INFINITE SERIES [Chap. 

and bo on. This is true no matter how we choose the points 05„. 
We can therefore reduce the idea of a convergent improper integral 
to that of an infinite series in many ways. 

It is especially convenient to choose the points as, in such a 
way that the integrand does not change sign within any indi- 

00 

vidual sub-interval. The series S | a„ | will then correspond to 

K=l 

the integral of the absolute value of our function, 

jf|/(aO|cfa. 

We are thus naturally led to the following concept: an improper 

X 00 
f (x)dx is said to be absolutely convergent if the integral 

|f(x) | dx exists. Otherwise, if our integral exists at all, we 

say that it is conditionally convergent. 

Some of the integrals considered earlier (pp. 250-251), such as 

/•" 1 r 00 a r m 

/ 7- — .dx, I e-^dx, V(x)= e-'t®- 1 *, 
Jo l + X* Jo Jo 

are absolutely convergent. On the other hand, the integral 

Jp°° sins , ,. r A sin* , 
! dx = hm / dx, 
o x ^->oo Jo £ 

studied on p. 251, is a simple example of a conditionally convergent integral. 
In order to give a proof of the convergence of this integral which is inde- 
pendent of the former proof, we subdivide the interval from to A at the 
points x v — vtc(v = 0, 1, 2, . . . , jj.^) where \x A is the largest possible in- 
teger for whioh \l a tz g A. We therefore divide the integral into terms of 

/"" r sin* 
the form a v = / dx{y = 1, 2, . . .), and a remainder R A of the form 

f -fH^tfce (0 g A — y.jit < 7t). 

It is clear that the quantities a v have alternating signs, since sins 
is alternately positive and negative in consecutive intervals. Moreover, 
| a^+j | < | a v |; for on applying the transformation x = 5 — tz, we have 

[sins | ^ = /•("+!> |sin(g-7r)| = X^+D- | sm g[ 

Jim 5 — W Jvk 5 — n 



J(v—Vfr 



ffr+l>| single 



VIII] IMPROPER INTEGRALS 4*9 

Hence by Leibnitz's test we see that £a v converges. Moreover, the 
remainder B A has the absolute value 



^ 1 /-^ + i> 2 

:g / sins \ ax = , 

few.,, H* TC 



and this tends to as 4 increases. Thus if we let A tend to « in the 

equation 

C^sinie r „ 

I da; = % + <% + a, + . . . + o„ + ic^, 

Jo x A 

the right-hand side tends to Ea„ as a limit, and our integral is convergent. 
But the convergence is not absolute; for 

, , f I sinal , 2 ,„,,,. 

\a v > / dx = — , so that 21 a, diverges. 



3. Infinite Pboduots 

In the introduction to this chapter (p. 366), we called atten- 
tion to the fact that infinite series are only one way, although 
a particularly important way, of representing numbers or func- 
tions by infinite processes. As an example of another such 
process, we shall introduce the infinite product. No proofs will 
be given. 

On p. 223 we met with Wallis's product, 

w = 2 2 4 4 6 6 
2 1'3'3'5'5*7"* 

in which the number w/2 is expressed as an " infinite product ". 
By the value of the infinite product 

00 

II a„ = Oj . Oa . a 3 . a 4 . . . 

we mean the limit of the sequence of partial products 

«!, % . Og, Oj . Oj . Og, «! . a 2 . a 8 . a 4 , ...» 

provided it exists. 



430 INFINITE SERIES [Chap. 

The factors a^, a 2 , a 3 , . . . , of course, may also be functions 
of a variable x. An especially interesting example is the " infinite 
product " for the function sinsc, 



sinwa;= 77a; 



(*-©(>-»(-» 



which we shall obtain in § 4 of the next chapter (p. 445). 

The infinite product for the " zeta function " plays a very important 
part in the theory of numbers. In order to retain the notation usual in 
the theory of numbers we here denote the independent variable by «, and 
we define the zeta function f or a > 1 by the expression 

We know (cf. § 2, p. 380 et seq.) that the series on the right converges if 
8 > 1. If p is any number greater than 1, we obtain the equation 

^~1 =sl+ p> + p Ts + p T.+ "- 
P* 
by expanding the geometric series. If we imagine this series written 
down for all the prime numbers p t , p v p& . . . in increasing order of 
magnitude, and all the equations -thus formed multiplied together, we 
obtain on the left a product of the form 



1-Pi- 1-Pf 

It, without stopping to justify the process in any way, we multiply to- 
gether the series on the right-hand sides of our equations, and in addition 
remember that by an elementary theorem each integer n > 1 can be ex- 
pressed in one and only one way as a product of powers of different prime 
numbers, we find that the product on the right is again the function 
£(«), and so we obtain the remarkable " product form " 

r^ 1 * 1 

This " product form ", the derivation of which we have only briefly 
sketched here, is actually an expression of the zeta function as an infinite 
product, since the number of prime numbers is infinite. 

In the general theory of infinite products we usually exclude 
the case where the product a^ • • • a « nas * ne 1™"* zer0 * Hence 
it is specially important that none of the factors a„ should vanish. 
In order that the product may converge, the factors a n must 



VIII] INFINITE PRODUCTS 421 

accordingly tend to 1 as n increases. Since we can if necessary 
omit a finite number of factors (this has no bearing on the ques- 
tion of convergence), we may take it that a n > 0. The following 
theorem applies to this case: a necessary and sufficient con- 

00 

dition for the convergence of the product II o„, where o„ > 0, 

00 V=l 

is that the series S logo„ should converge. For it is clear that 

n 

the partial sums Sloga y = log {c^a^ . . . a») of this series will 

v=l 

tend to a definite limit if, and only if, the partial products 
a^a 2 . . . a n possess a positive limit. 

In studying convergence we usually apply the following 
criterion (a sttfficient condition), where we put a, = 1 -J- a„. The 

00 
product II (1 + a„) 



converges, if the series 



=1 



S|a„ 



converges and no factor (1 -f- a„) is zero. In the proof we may 
assume, after omission of a finite number of factors if necessary, 

that each | a y | < -. Then we have 1 — | a„ | > -. By the 

1 

mean value theorem log(l + h) = log(l + h) — logl = h 

1 -+- 6h 

for < < 1. Therefore 
I log(l + «,)!■ 



l+0a„ 

00 

and so the convergence of the series 2 log (1 -J- «„) follows from 

00 K«»l 

the convergence of 2 | a„ |. 
„=i 

Prom our criterion it follows that the infinite product given above for 

sin nx converges for all values of x except for x = 0, ±1, ±2 where 

factors of the product are zero. Moreover, for p ^ 2 and * > 1 we readily 
find that 

1 , , 1 1 2 

1 — p-» p* — 1 p' — 1 p' 



422 INFINITE SERIES [Cha*. 

Now if we let p assume all prime values, the series S— must converge, 



P° 



00 1 

since its terms form only a part of the convergent series S — . The oon- 

vergence of the product II for a > 1 is thus proved. 

I — p-» 



4. Seeies involving Beenoulli's Numbees 

So far we have given no expansions in power series for certain elemen- 
tary functions, e.g. tana;. The reason is that the numerical coefficients 
which occur are not of any very simple form. We can express these 
coefficients, and those in the series for a number of other functions, in 
terms of the so-called Bernoulli's numbers. These numbers are certain 
rational numbers, with a not very simple law of formation, which occur 
in many parts of analysis. We arrive at them most simply by expanding 
the function 

x 1 

1 + 2! + 3! + -'- 



in a power series of the form 



s ^v. 



e»-l „-ov! 
If we write this equation in the form 

00 n 

*—(e»- 1) 2 —x" 

and substitute on the right the power series for fs" — 1, we obtain, as on 
p. 417, a recurrence relation which enables all the numbers B„ to be 
calculated. These numbers are called Bernoulli's numbers.* They are 
rational, since in their formation only rational operations are concerned; 
as we easily recognize, they vanish for all odd indices other than v = 1. 
The first few are 



JL - 5 

30' 



B * = — nn > 5 io = HH> • • • 



* In some works a slightly different notation is used, the basio formula being 
written 

— - i - i- + v /_ iy+1 -Ql x *» 

e»- 1 2 X „_i ( l; (2v)l !E • 



VIII] BERNOULLI'S NUMBERS 4*3 

We must content ourselves with a brief hint as to how these numbers 
are involved in the power series in question. First, by m akin g use of the 
transformation 

B 2 x ,"_x e?+ 1 _ x el* + e~** 

1 + 2[ * + •••=■ jTTi + 2 ~ 2 " e^~l "" 2 " e** - e~** 

we obtain 

?coth?= 2 ^fx". 
2 2 „= (2v).' 

If we replace x by 2x, we have the series 

00 OScR 
iBCOth*= S ~^**% 

v- o (2v)! 
for |*| < 7T, from which, by replacing x by — &r, we obtain 

* cot* = 2 (-1)* ^%**, I x I <k. 

By means of the equation 2 cot 2* = cot a; — tana; we now obtain the 
series 

co 2 a "f2 2 " — l\ 

tans = 2 (-1)- 1 \ 9 ., ^ a^- 1 . 
-=i (2v)! 

which holds for I x I < -. 
1 ' 2 

For further information we must refer the reader to more detailed 

treatises,* owing to the lengths of the proofs involved. 



Examples 

1. Prove that the power series for V(l — x) still converges when 
*= 1. 

2. Prove that for every positive e there is a polynomial in x which 
represents V(l — x) in the interval ^ x ^ 1 with an error less than e. 

3. Prove that for every positive e there is a polynomial in ( which 
represents 1 1 1 in the interval — 1 g t ^ 1 with an error less than s. 

4. Weierstrasa' Approximation Theorem. Prove that if f(x) is con- 
tinuous in a ^ x ^ 6, then for every positive e there exists a polynomial 
P(x) such that \f(x) — P(x)\ < e for all values of x in the interval 
o ^ x ^ &. 

5. Prove that the following infinite products converge: 

n (i + <$)*»); n !Lz_j n (i - -), a | «i< l. 

»-i n-a n s + 1 n-l * »/ 

* See e.g. K. Knopp, Theory and Application of Infinite Series, p. 183 (Blackie 
ft Son, Ltd., 1928). 



424 INFINITE SERIES [Chap. VIII 

6. Prove by the methods of the text that II [ 1 -f- - ) diverges. 

7. Using the identity 

"1 " / 1 \ 

2 - = II ( ) (where p { is the t-th prime) 

»_i n* t-i \1 — p t ~*J 



Pi 

prove that the number of primes is infinite. 
8. Prove the identity 

1 



n (1 + a; 2 ") = 



v=l 1—35 

for |*| < 1. 



CHAPTER IX 
Fourier Series 

In addition to the power series there is another class of 
infinite series which plays a particularly important part both 
in pure mathematics and in applications. These are the Fourier 
series, in which the individual terms are trigonometric functions 
and the sum is a periodic function. 

1. Periodic Functions 
1. General Remarks. 

Periodic functions of the time, that is, functions which repeat 
their course after a definite interval of time, are met with in 
many applications. In most machines a periodic process takes 
place in rhythm with the rotation of a flywheel, e.g. the alter- 
nating current developed by a dynamo. Periodic functions are 
also associated with all vibration phenomena. 

A periodic function with period 21 is represented by the equation 

f(x+2l)=f(x), 

true for all values of x. We specially call attention to the fact that 
21 is called the period* It is worth notice that in addition to 
the period 21, the function f{x) necessarily has the period U 

* In representing periodic functions it is often convenient to denote the 
independent variable * by a point on the circumference of a circle instead of 
the usual point on a straight line. If a function f(x) has the period 2ir, say, 
that is, if the equation 

f{x + 2*)-f(x) 

is true for all values of x, and if we denote by x the angle at the centre of a circle 
of unit radius which is included between an arbitrary initial radius and the 
radius to a variable point on the circumference, then the periodicity of the 
function /(a;) is expressed simply by the fact that to each point on the circum- 
ference there corresponds just one value of the function. In the case of a 
machine, for example, the periodicity may be expressed in terms of the position 
of a point on the flywheel. 

425 



426 FOURIER SERIES [Chap. 

also, since f(x+4l)=f(x+2l)=f(x); f(x) likewise has periods 
6Z, 81, ... ; and it is also possible (though not necessarily true) 
that f(x) may have shorter periods, such as I or J/5. Graphically, 
in any two consecutive intervals of length 21 the graph of the 
function has exactly the same form. In order to have available 
a second interpretation which some readers may prefer, we may 
think of the variable x as the time (and accordingly we some- 
times write ( instead of x), the function f(x) then representing a 
periodic process or, as we shall also say, a vibration (or oscil- 
lation). The period 21 = T is then called the period of vibration 
(or oscillation). 

If any arbitrary function i (x) is given in a definite interval, 
sa y> — I ^ x ^ I, it can always be extended as a periodic function; 
we have only to define f(x) outside the interval by the equation 
f(x + 2nl) =f(x), where n is an arbitrary positive or negative 
integer. Here we must point out that if f{x) is continuous in 
the interval — I <L x ^ I, but /(— 1) =# f(+l), our extended 
periodic function will be discontinuous at the points +1, +21, . . . , 
(cf. figs. 7 and 8 (pp. 441, 442), in which I = -n). Further, in 
this case the extension fails to give us a single- valued function 
f(%) at the points x = ±1, +3J, . . . since e.g. we have defined 
f{2>l) as f(l -f 21), which gives /(3?) = f(l), and we have also 
defined it as /(— I + U), which gives f(3l) ==/(— I). We avoid 
this difficulty by extending, not the function as defined for 
—l^x^l, but the function as defined either for — I < x 5S I 
or — I j£ x < I; that is, we discard either the original value 
f(—l) or the original value f(+l). 

Here we would point out a general fact relating to periodic 
functions, which is expressed by the equation 

/, f(x)dx = f f(x)dx, 

or, in words: the integral of a periodic function over an interval 
whose length is one period T = 21 always has the same value, 
no matter where the interval lies. To prove this we need only 
notice that in virtue of the equation f(£ — 21) =/(£) the sub- 
stitution x = £ — 21 gives us 

f(x)dx=J f(£)d£=J f(x)dx. 



IX] PERIODIC FUNCTIONS 427 

In particular, for a = — I — a and /? = — I it follows that 

J , /(a) dx = f f(x) dx, 

J —l— a J I— a 



and hence 

r l-a 



f f(x)dx=f~ f(x)dx + f~"f(x)dx 

pi pi — a pi 

=J l _J( x ) dx +j f( x ) dx =J_ l f( x ) dx > 

which proves our statement. If we recall the geometrical meaning 
of the integral, the statement is made obvious by fig. 1. 




Fig. i. — To illustrate the integral over a whole period 



The simplest periodic functions, from which we shall later 
build up the most general periodic functions, are the functions 
a sinoxr and a cos cock, or more generally a sin w (x — £) and 
a cosco(x — f ), where a(2:0), <u(>0), and £ are constants. The 
processes represented by these functions * we call sinusoidal 
vibrations or simple harmonic vibrations (or oscillations). The 
period of vibration is T = 2irlw. The number a> is called the 
circular frequency of the vibration; -f since 1/T is the number of 
vibrations in unit time, or frequency, w is the number of vibra- 
tions in time 2n. The number a is called the amplitude of the 
vibration; it represents the maximum value of the function 
a sinaj(a; — £) or a cosco(a; — £), since both sine and cosine have 
the maximum value 1. The number co(x — |) is called the phase 
and the number wg the epoch or phase displacement. 

* Either of these formulae taken by itself (for all values of a and £) represents 
the class of all sinusoidal vibrations; and the two formulae are equivalent to 
one another, since asinco(x — f) — acos<x>{x — (( + tt/2o>)}. 

t The reader should take care to distinguish between the frequency and the 
circular frequency (Ger., Kreisfrequem). 



428 



FOURIER SERIES 



[Chap. 



We obtain these functions graphically by stretching the sine curve 
in the ratios 1 : o along the a;-axis and a : 1 along the j/-axia, and then 
translating the curve a distance ij ™ the positive direction along the 
s-axis (cf. fig. 2). 

By the addition formulae for the trigonometric functions we 
can also express sinusoidal vibrations in the form 

a coswx -f- /} sinaxt and j3 coswas — a sinwx 




Fig. 2. — Sinusoidal vibrations 



respectively, where a = — a sincuf and jS = o cos<o£. Con- 
versely, every function of the form 

a cosgjx + fi sinwa; 

represents a sinusoidal vibration a sinco(a; — f) with the ampli- 
tude a= \/(a?-\- /J 2 ) and the phase displacement w£ given by the 
equations a = — a sinw|, /$ = a cosa>|. By using the expression 
a cosajcc + ft sin <mx we see that the sum of two or more such 
functions with the same circular frequency o> always represents 
another sinusoidal vibration with the circular frequency a>. 



2. Superposition of Sinusoidal Vibrations. Harmonics. 

Although many vibrations are found to be sinusoidal 
(cf . Chap. V, § 4, p. 296), it is nevertheless true that most periodic 
motions have a more complicated character, being obtained by 
the superposition of sinusoidal vibrations. Mathematically this 



IX] PERIODIC FUNCTIONS 429 

simply means that the motion, e.g. the distance of a point from 
its initial position as a function of the time, is given by a function 
which is the sum of a number of pure periodic functions of the 
above type. The sine waves of the function are then piled 
up on top of one another (that is, their ordinates are added), 
or, as we say, they are superposed. In this superposition 
we assume that the circular frequencies (and, of course, the 
periods) of the superposed vibrations are all different; for the 
superposition of two sinusoidal vibrations with the same circular 
frequency gives us another sinusoidal vibration with the same 
circular frequency (but with a different amplitude and phase 
displacement), as shown above. 

If we consider the simplest instance, the superposition of 
two sinusoidal vibrations with the circular frequencies ci> x and u> 2 , 
we find that there are two fundamentally different cases, depend- 
ing on whether the two circular frequencies have a rational ratio 
or not, or, as we say, whether they are commensurable or in- 
commensurable. We begin with the first case, and by way of an 
example take the second circular frequency to be twice the first; 
to 2 = 2^. The period of the second vibration will then be half 
the period of the first, 2^/20)! = T % = TJ2, and so it will neces- 
sarily have not only the period T 2 but also the doubled period T x , 
since the function repeats itself after this double period; and the 
function formed by superposing them will also have the period 
T v The second vibration, with twice the circular frequency and 
half the period of the first, is called a first harmonic of the first 
vibration (the fundamental). 

Corresponding statements hold if we introduce a further 
vibration with the circular frequency w 3 = 30^. Here again the 
vibration function sin 3^3; will necessarily repeat itself with the 
period 2^/^ = T x . Such a vibration is called a second harmonic 
of the given vibration. Likewise we can consider third, fourth, . . . , 
(n — l)-th harmonics with the circular frequencies a> 4 = 4*u 1; 
o) 5 = 5ft*!, . . . , <o„ = nco v and, moreover, with any phase dis- 
placements we please. Every such harmonic will necessarily 
repeat itself after the period T r = 2-n\ot x , and consequently every 
function obtained by superposing a number of vibrations, each 
of which is a harmonic of a given fundamental circular frequency 
<xt v will itself be a periodic function with the period 2tt\u> x = T v 
By superposing vibrations with circular frequencies ranging from 



43° 



FOURIER SERIES 



that of the fundamental to that of the (n ■ 
obtain a periodic function of the form 



[Chap. 
l)-th harmonic we 



S (x) = a + 2 (a„ cos vcox + 6„ sin vwx). 




Fig. 3*. — Combination of vibrations 



(The constant a, which we have introduced here in order to make 
the formula slightly more general, does not affect the periodicity, 
since it is periodic for any period.) Since this function contains 




sin 2* 



sm*-5% 2 *+ 8 J n A* 

i 3 
j_ sin 2» , sin Sx _ sin 4» 

2 3 4 

Fig. 4. — Combination of vibrations 



2n -f- 1 constants which we can choose arbitrarily, we are thus 
able to generate very complicated curves which are not at all 
like the original sine curves. Figs. 3-5 illustrate this graphically. 

* The proportions of the figure correspond to the assumption at - 1. 



IX] 



PERIODIC FUNCTIONS 



43i 



The term " harmonic " originates in acoustics,* where we find 
that if a fundamental vibration with circular frequency a> corre- 
sponds to a note of a certain pitch, then the first, second, third, &c, 
harmonics correspond to the sequence of harmonics of the funda- 
mental, that is, to the octave, octave -f- fifth, double octave, &c. 

In general, in the case of 
the superposition of vibra- 
tions in which the circular 
frequencies have rational 
ratios these circular fre- 
quencies can all be repre- 
sented as integral multiples 
of a common fundamental 
circular frequency. The 
V>\ superposition of two vibra- 




^ 



Fig. St. — Combination of vibrations 



tions with incommensurable circular frequencies <a 1 and <w 2 , 
however, represents an intrinsically different type of pheno- 
menon. Here the process resulting from the superposition of 
sinusoidal vibrations will no longer be periodic. We cannot go 
into the mathematical discussions that arise from this, but 
merely remark that such functions always have an approxi- 
mately periodic character, or, as we say, are almost periodic. 
Such functions have just recently been studied in great detail. 

A final remark on the superposition of sinusoidal vibrations 
is concerned with the phenomenon of so-called beats. If we 
superpose two vibrations both with unit amplitude but with 
different circular frequencies a> 1 and w z , and if for the sake of 
simplicity we take the same value of | (see p. 427) for both (the 
generalization to arbitrary phase can be left to the reader), then 
we are merely concerned with the behaviour of the function 

y = saiw-jX + amourfc (o> x > w 2 > 0). 

* In acoustics the terms overtone, (tipper) partial are also used, 
t The curves drawn in the figure correspond to the trigonometrical poly- 
nomials obtained by taking 3, 5, 6 and 7 terms respectively of the series 
sins , 2 sin 2a; . gin 3s sin 5a ; „ sinoa; . sin 7a; , sinto 
1 2 3 5~ 6~~ ~T~ ~T" 



432 FOURIER SERIES [Chap. 

By a well-known trigonometrical formula we have 
y = 2 cos^toj — o> 2 )x sin^ajj + <o 2 )x. 

This equation represents a phenomenon which we may think of 
as follows: we have a vibration with the circular frequency 
^(o> x + w 2 ) and the period in/^ + o> 2 ). This vibration, how- 
ever, has not a constant amplitude; on the contrary, the " am- 
plitude " is given by the expression 2C0SKWJ — cd 2 )x, which 
varies with a longer period 477/(0^ — o) 2 ). This point of view is 
particularly useful and easy to interpret when the two circular 
frequencies ca 1 and co 2 are relatively large while their difference 



Fig. 6. — Beats 

(a^ — w 2 ) is small compared to them. Then the amplitude 
2 cos^t^i — oj 2 )x of the vibration with period ^/(toj + <o 2 ) 
will vary only slowly compared with the period of vibration, and 
this change of amplitude will repeat itself periodically with the 
long period ^/(a^ — o> 2 ). These rhythmic changes of amplitude 
are called beats. Everyone is acquainted with this phenomenon 
in acoustics and perhaps also in wireless telegraphy. In wireless 
telegraphy the circular frequencies a^ and w 2 are as a rule far 
above those which the ear can detect, while the difference 
w i — '"a f au,s m * ne ran g e 0I audible notes. The beats then cause 
an audible note, while the original vibrations remain imper- 
ceptible to the ear. 

An example of beats is illustrated graphically in fig. 6. 



IX] COMPLEX NOTATION 433 

2. Use of Complex Notation 

1. General Remarks. 

The investigation of vibration phenomena and periodic func- 
tions gains in formal simplicity if we make use of complex num- 
bers, combining each pair of trigonometric functions cos cox and 
sincua; to form an expression of the type cosoxz; -f- i sincox = e"** 
(cf. Chap. VIII, § 7, p. 411). Here we must bear in mind that one 
equation between complex quantities is equivalent to two equa- 
tions between real quantities, and that our results must always 
be interpreted and made intelligible in the real domain. 

If we everywhere replace the trigonometric functions by 
exponential functions in accordance with the formulas 

2 cos 6 = (3* + e-' e , 2t sin 6= <?* — er ie , 

we express sinusoidal vibrations in terms of the complex quan- 
tities e'"*, er™*, or 

ae t„c*-8 ae -t»(*-{) 

respectively, where a, to, and to£ are the real quantities ampli- 
tude, circular frequency, and phase displacement. The real 
vibrations are obtained from this complex expression simply by 
taking real and imaginary parts. 

The convenience of this mode of representation for many 
purposes is due to the fact that the derivatives of the real vibra- 
tions with respect to the time x are obtained by differentiating 
the complex exponential function just as if i were a real con- 
stant, as is expressed by the formula 

— a{ cosw (a; — £) + i sinw (x — £) } 
ax 

= aw{ — sina>(a; — £) + t cosoj(a; — £)} 
= iato{ coato(x — £) + i sinco (x — £)}, 

or — a^"- & = wto^*-®. 

dx 

2. Application to the Study of Alternating Currents. 

We shall now illustrate these matters by means of an important 
example. Here we shall denote the independent variable, the time, by t 
instead of x. 

Jf (K798) 



434 FOURIER SERIES [Chap. 

We consider an electric circuit with resistance B and inductance L, 
on which an external electromotive force (voltage) E is impressed. In the 
case of direct current E is constant, and the current / is given by Ohm's 
law, 

E = BI, 

If, however, we are dealing with alternating current, E is a function of 
the time t, and consequently so is J, and Ohm's law takes the form (cf. 
p. 182) 

E-L^ = BI. 

dt 

In the simplest case, to which we restrict ourselves here, the external 
electromotive force E is sinusoidal with circular frequency co. Now instead 
of taking this oscillation in the form a oosat or a sin<oi, we combine both 
possibilities formally in the complex form 

E = se'"' = e coscaf + *s sintat, 

where e( >0) represents the amplitude. We shall operate with this " com- 
plex voltage " as if i were a real parameter, and we thus obtain a complex 
current /. Then the significance of the relation thus found between 
the complex quantities E and / is that the current corresponding to an 
electromotive force e cos<ot is the real part of J, while the current correspond- 
ing to an electromotive force e sincoi is the imaginary part of /. The com- 
plex current can be calculated immediately if for I we write down an 
expression of the form 

/ = ae"""' = a(cos&>« + i sin<o<); 

that is, if we make the assumption that / is also sinusoidal with circular 
frequency <o. The derivative of / is then given formally by the expression 

dl . . , 
dt 

= aa>(— sino>< + icoscot). 

By substituting these quantities in the generalized form of Ohm's law and 
dividing out the factor e""t we obtain the equation e — aiito = Ba, or 



B + uaL 
so that E = (B + iaL)I = WI. 

We may regard this last equation as Ohm's law for alternating currents 
in complex form, if we call the quantity 

W = B + iaL 

the complex resistance of the circuit. Ohm's law is then the same as for 
direct current: the current is equal to the voltage divided by the resistance. 



IX] COMPLEX NOTATION 435 

If we write the complex resistance in the form 
W = we is = w cosS + iv> sin 8, 



where 



we obtain 



V(i2 2 + LW), tan 8 = ^, 



v> 



According to this formula the current has the same period (and circular 
frequency) as the voltage; the amplitude a of the current is connected 
with the amplitude e of the electromotive force by the equation 

e 
w 

and, in addition, there is a difference of phase between the current and the 
voltage. The current reaches its maximum, not at the same time as the 
voltage, but at a time 8/to later, and the same is of course true for the 
minimum. In electrical engineering the quantity w = Vf-R 2 + £ 2 <o 2 ) is 
frequently called the impedance or alternating current resistance of the 
circuit for the circular frequency oi; the phase displacement, usually stated 
in degrees, is called the lag. 



3. Complex Representation of the Superposition of Sinusoidal 
Vibrations. 

So far the complex notation has been used to denote the com- 
bination of two sinusoidal vibrations. But a single vibration or a 
compound vibration of the type 

n 

S(x) = a + S (a„ cosv^c + b y sin vx) 

(for simplicity we have taken co = 1) can also be reduced to com- 
plex form by substituting 

cosra = - {£"* + e- ,v *) 

and sin vx = — . (e ,v * — e~ ivX ). 

The above expression then becomes an expression of the form 
S(x) = 2 a v e iv *, 



43<S FOURIER SERIES [Chap. 

where the complex numbers a„ are connected with the real 
numbers a, a„ and 6„ by the equations 

a v = a v + a--v> a- = <* , b v = i(a„ — a_ v ). 

In order that the equation a v = a„ + a_„ shall formally include 
the case v = 0, we often put a = Oq = a /2. 

Conversely, we may regard any arbitrary expression of the 
form 

S a„e ,v * 

as a function representing the superposition of vibrations, written 
in complex form. In order that the result of this superposition 
may be real it is only necessary that a„ -f- a_„ should be real and 
a, — o_„ a pure imaginary; that is, a v and a_„ must be con- 
jugate complex numbers. 

4. Deduction of a Trigonometric Formula. 

By using complex notation we obtain a very simple proof of a formula 
which we shall need later. This is the trigonometric summation formula 

<*»(«) = i + °os<* + cos2a + . . . + coswa = ! m ( w + i)« 

2 sin J a 

which is true for all values of a except the values 0, ±2n, ±4tt, .... 
To prove this we replace the cosine function by its exponential ex- 
pression and thus bring the sum a„(a) into the form 

a„(a) = J 2 ««■». 

On the right we have a geometric progression with the common ratio 
q = e 1 '" =t= 1. Using the ordinary formula for the sum, we have 

„ (a) = I e - im 1 ~ g 2n+1 = 1 «^»-e6.+i» 
" 2 l- 3 2 1 - e« * 

On multiplying numerator and denominator by e~ ,a / 2 we obtain 

c a (a) = !H^ + i^ 
2sin£<x 

as was stated. 



IX] COMPLEX NOTATION 437 

Examples 

1. Sketch the curves w = 2 for N = 3, 5, 6. 

n-i n 

n cos/ 

2. Sketch the curves y = 2 — - for N = 3, 6, 8. 

3. Evaluate the sum sin a + sin 2a + — + sinraa. 

4. If s m (a) = C ° (a) + CT i( a > + • • • + a ™(* ) where c„(a) has the value 

c n ( a ) = J + cos a + cos 2a + . . . + cos»a, prove that 

(m+ l)a"i a 



fl » (a)== ^Tl 



sin- 



. a 

sm- 

2 



(The expression s m is called the " Fejer kernel ", and is of great importance 
in the more advanced study of Fourier series.) 

5. Show that * f\ m(a )da=l, 

where s m {tx) is the Fejer kernel of Ex. 4. 

3. Fourier Series 
The function 

n 

S(x) = a + S (a„ cos va + 6„ sinva;) 

resulting from the superposition of sinusoidal vibrations contains 
2n + 1 arbitrary constants a, a„, 6„. The question now arises 
whether these constants can be so chosen that in the interval 
—it ^x^tt the sum S(x) shall approximate to a given function 
f(x), and if so, how they are to be found. More precisely, we 
inquire whether the given function /(a;) can be expanded in an 
infinite series 

00 

f(x) = a + 2 (a„ cos vx + b v sin vx). 

If we assume for the moment that this expansion of the 
function f(x) is actually possible and that the series converges 
uniformly in the interval — it ^ x 5S it, we readily obtain a 
simple relation between the function fix) and the coefficients 
a = £a , a„ and b r . (We shall soon see that the notation a = £a 



43» FOURIER SERIES [Chap. 

is justified by its convenience.) We multiply the hypothetical 
expansion above by cos vx and integrate term by term, as is per- 
missible on account of the uniform convergence. In virtue of the 
orthogonality relations 

r + ". . 7 (0, if m =fe n, 

J sm mx smnxdx = \ 
J -n \tt, ifm=n4=0. 



/' 



sin mx cosnxdx = 0, 



- + *_ j_ (0, ifm4=n, 

if m= n, 



/ cos mx cosnxdx = \ 

J -„ \1T, 

proved in Chap. IV, § 3 (p. 217), we at once obtain the formula 

1 r +7r 
o„ = - / f(x) cos vxdx 

for the coefficients. Similarly, by multiplying the series by sin vx 
and integrating, we have 

1 r + " 
6„ = _ / f(x) sin vxdx. 

These formulae assign a definite sequence of coefficients 
a v and b v , usually called the Fourier coefficients, to every 
function f(x) which is defined and continuous in the interval 
— tt ^ x 5S it, or has only a finite number of jump discontinuities 
there. If the function f(x) is given, we can use these quantities 
a„, b v to form the Fourier partial sums 

n 

S„ (x) = %a -f- 2 {a v cos vx -f 6„ sin vx), 

and we may also formally write down the corresponding infinite 
" Fourier series ". Our problem is to distinguish simple classes 
of functions /(x) for which this Fourier series does actually con- 
verge and does represent the function. 

In order to formulate the result which we wish to prove, we 
introduce the following definition. A function f(x) is said to be 
sectionally smooth * in an interval if it is itself sectionally 
continuous f (that is, continuous in the interval except for a 

* Ger. stllckweise glatt. f Ger. gtiichweise stetig. 



IX] FOURIER SERIES 439 

finite number of jump discontinuities) and if in addition its first 
derivative f'(x) is sectionally continuous. 

We shall imagine the function /(a;) originally defined in the 
interval — -n ^ x 5£ 77 to be periodically extended. 

At each point at which the function /(x) has a jump discon- 
tinuity we shall alter the function, if necessary, and shall assign to 
it the value which is the arithmetic mean of the left-hand limit 
and the right-hand limit oif(x); that is, we write 

/(*) = *(/(*-0)+/(a! + 0)), 

where f(x — 0) and f(x -f 0) are simply the limits of f(x) as x 
approaches x from the left and from the right respectively. This 
equation is obviously true for every point x at which f(x) is con- 
tinuous. 

Our goal is the following theorem: 

If the function f (x) is sectionally smooth and satisfies the above 
equation, then its Fourier series converges at every point x and 
represents the function.* 

Further, we shall prove the following theorem: 

In every closed interval in which the function f(x) (imagined 
periodically extended) is continuous as well as sectionally smooth, 
the Fourier series converges uniformly. 

Finally: 

If the function f (x) is sectionally smooth and has no dis- 
continuities, the Fourier series converges absolutely. 

The proofs of these theorems will be postponed until § 5 
(p. 447). Here we merely wish to emphasize that the functions 
which can be expanded according to these theorems have a very 
high degree of arbitrariness; it is by no means necessary that 
the functions should be given by a single analytical expression. 

In the next section we shall display the extraordinary 
fertility of the Fourier expansion by discussing a number of 
examples. 

* It may be remarked incidentally that this theorem can be proved for 
more general classes of functions. The result formulated here, however, suffices 
for all applications. 



44° FOURIER SERIES [Chap. 

4. Examples of Fourier Series 

I. Preliminary Remarks. 

We shall assume that our functions f(x) have the period 2tt 
and are denned in the interval — v < x < v. Beyond this interval 
to the left and the right, they are to be extended periodically, 
as on p. 426. 

Before going into details we remark that if f{x) is an even 
function (cf. p. 20), then clearly f(x) suike is odd and f(x) 
cos vx is even, so that 

b„ = - / f(x) sin vxdx = 0; a v = / f{x) cos vxdx. 

TrJ—w TT"'0 

We thus obtain a " cosine series ". If, on the other hand, the 
function f(x) is an odd function, then 

1 r +1r 2 r" 

a„ = - / f(x) cos vxdx = 0; 6„ = - / f(x) sin vxdx. 

We therefore obtain a " sine series ".* 



2. Expansion of the Functions \\>(x) — x and <p(x) = X 2 , 

id lunction x we nave o„ = 
tion by parts 



For the odd function x we have &„ = - /a; sinvsda;, and on integra- 
nt J 



It, — xoosvs 
-b„ = 



+ - feosvxdx = (-1)" +1 -. 
v Jo v 



Hence for the periodic function <\i(x) which in the interval — 7t < x < it is 
equal to x (cf. fig. 7) we obtain the expansion 

i / > « fsinx sin2a; , sin3« , \ 

+ (*)-2(— _ + _- + ...]. 

If we put x = 7t/2 we obtain Gregory's series, 

"=1-1 + 1- + ..., 
4 3 5 

with which we are already familiar (p. 319). The function i/(%) represented 
by this series is not a continuous function; on the contrary, it jumps by 

* Consequently, if the function f(x) is initially given only in the interval 
< x < 7t, then we can extend it in the interval — w < x < either as an 
odd function or as an even function, and correspondingly expand the function 
in the interval < x < jt either in a sine series or in a cosine series. 



IX] 



EXAMPLES 



441 



an amount 2n at the points x = kn, k = ±1, ±3. ±5 At these 

points of discontinuity, that is, at the points x = kit, k= ±1, ±3, ±5, . . . , 
each term of the series is zero, and hence the function itself is zero. Hence 
at the points of discontinuity the series represents the arithmetic mean 
of the left-hand and right-hand limits. 

If 5 is any fixed number between — 7c and it, and if we replace x in the 
above series by (x — £), we obtain the series 

«h* - a = 2 ( sin(a: - * > - sin2( * ~ g) + sin3(a: ~ %) - + . . .) 

\ 1 if o / 

2 2 2 

= — - sinE cosa: + - cosE sina; + - sin25 cos2a: 
1 1 2 

2 2 2 

— cos2E sin2a: — - sin3E cos3a: + - cos3E sin3z + . . . . 
2 3 3 




Fig. 7 



This may also be written in the form of a Fourier series with coefficients 



0, a„=2 



(-1)" • 



sinwJ;, b n = 2 



= 9.(-l)" 



COS 71 5, 



which tend to zero as n increases; this series represents a function having 

the discontinuities described above at the points a;=5±7r, i=E ± 3n 

For the even function <p(x) = a? we find, on integrating by parts twice, 
that 

a„=- C x* cosva:cte = (— I)" - (v > 0), 

TZJ V 2 

27t 2 



so that we obtain the expansion 



cp (x) = — 
y\ i 3 



cosa; cos 2x cos 3a; 
~2?~ ~W 



(cosa; 



- + 



> 



By differentiating this series term by term and dividing by 2 we formally 
recover the series for f ]i{x) = x. 



15« 



;i798) 



442 



FOURIER SERIES 



[Chap. 



3. Expansion of the Function .r cos at. 

For this odd function we have 

2 /•" 

a„ = 0, b r = - / a; cosa; sinvaiix. 
■a J 
By using the formula 



•'o 



aia i ixdx= (— l)e+i - (n = 1, 2, . . .) 



found in the previous sub-section, we evaluate 6„: 

b y = - I xcosxainvxdx= - I a;(sin(v + l) 31 + sin(v — l)x)dx 
tzJq t:J 



(— 1)"+ 2 (—1)- 2v 



6i=-; 




Fig. 8 



We therefore obtain the series 



1 



x cosa; = — - sina + 2 X 



2, (-l) P v . 



2 ,_, v* - 1 

and if -we add the series found on p. 440 this becomes 



smvas, 



... . 3 . , / sin2a; 

xll -f cosa;) = - sina; +21 — 
v ' 2 \l. 



sin3a; sin4a; , 



2.3 2.3.4 3.4.5 



)• 



When the function which is equal to x cos a: in the interval — -k < x < n 
is extended periodically beyond this interval, the same discontinuities 
(of. fig. 8) occur as are exhibited by the function <\>(x) considered in No. 2. 
On the other hand, if the function x(l + cos a:) is periodically extended it 
remains continuous at the end-points of the intervals, and in fact its deri- 
vative also remains continuous, since the discontinuities are eliminated 
by the factor 1 -f- cos a;, which together with its derivative vanishes at 
the end-points. 



IX] 



EXAMPLES 



♦43 



i. The Function f{ x) = \x\. 

This function is even; consequently 6, = and 
2 



o„ = - / x cos \>x dx, 

77 Jn 



and on integration by parts we readily obtain 



f 
Jo 



x cos va; dx = - x sin va; 
v 



* l r 

v -4 



sinvxix 



f 0, if v is even and 4= 0, 

= \ 2 

:, if v is odd. 



Consequently 



... 77 4 / , cos3cc , cos5a; , \ 

f{x) = 2 ~ * l 008 * + T + ~sr + • • •> 

If we put x = 0, we obtain the remarkable formula 

<L 3 =1 + I + A+.... 

8 T 3 ! 5' T 

5. Example. 

The function defined by the equations 

(—1, for — 7t < x < 0, 
0, for x = 0, 
+ 1, forO < x < it, 



m ^_^^^ 


y 






. .i 




-x\ 





-f 


Jl\ 


2jJI 


5 













Fig. 9 

as indicated in fig. 9, is an odd function. Hence a„ = and 

/ if v is even, 

b = - I sin vxdx= \ 4 

"Jo — if v is odd, 



so that the Fourier series for the function is 

,, , 4 (smx . sin3a; . \ 
/{x)= __[^_ + _+...j. 

For a; = ", in particular, this again yields Gregory's series. 

This series can be formally derived from that for | x | by term-by-term 
differentiation. 



H4 • FOURIER SERIES [Chap. 

6. The Function f(x) = | sin x \. 

The even function f(x) = | siux | can be expanded in a cosine series, 
the coefficients a y being given by the following calculation: 

7t /•" I /* 

- o„ = / srnxcosvxaJa; = - / {sin(v + \)x — sin(v — \)x}dx 

2 Jo ^ Jq 



' if v is odd, 
—2 



(.V s — 1 
We thus obtain 



if v is even. 



i - i 2 4 ? cos2ixa! 



k n^x 4(x a — 1 

7. Expansion of the Function cos y.x. Resolution of the Cotan- 
gent into Partial Fractions. The Infinite Product for 
the Sine. 

Let /(x) = cos [jue for — iz < x < tc, where y. is not an integer. Since 
f(x) is even we again obtain 6„ = 0, while 

7T z" 17 1 /" lr 

- a„ = / cosjjue cosvxcfa: = - / {cos(n + v)x + cos((ji — v)x}dx 

2 Jo "Jo 

_ 1 j sin(ti, + v)tc , 3in((i,— v)rc \ 

2 \ {x + v [i — v / 

|X(-1)" . 
(X 2 — V 2 

We thus have 

2u.sintATC / 1 cossc , cos2a: . \ 

«,.,«=__ ^_____ + ____ + ...j. 

This function remains continuous at the points as = ±tc. If we put x = jc, 
divide both sides of the equation by sin [i.7t, and then write x instead of \x, 
we obtain the equation 

2x( 1 , 1 , 1 , \ 

This is the so-called resolution of the cotangent into partial fractions, a very 
important formula frequently discussed in analysis. We now write this 
series in the form 



cot not 

■KX 



KT nil'-** 2»-s» / 



If x lies in an interval iS x :S <? < 1, the n-th term on the right is less in 

2 1 

absolute value than Hence the series converges uniformly in 

it n a — « 8 



IXJ EXAMPLES 445 

this interval, and can be integrated term by term. We thus obtain 

Jr* i 1\ sinra: ,. , sinrai sinra; 

1 (cotTrt J <« = log v^ lo 8 — — = lo S — — 

on the left, and 

^0-5) +k8 ( i -*) + ---5 n .ii ,Dg ( l -5) 

on the right, multiplying both sides by n. If we pass from the logarithm 
to the exponential function we have 

RimTX lim 2 k>g(l -«•/•'•> S log (1 -**/■.») 

warm = ^^ „_, = hm e — i 



TZX 

= lim 
Hence 



■h"w="w(i-y( i -J)( 1 -^)--- • 



We have thus obtained the famous expression for the sine as an^irifinite 
product.* Prom this, by putting x = -, we obtain Wallis's product 

7t_ » 2v 2v ^2 2 4 4 

2 ~ .i^v - 1 "2v+l — l'3'3"6'"" 
as on p. 224. 

8. Further Examples. 

By brief calculations similar to the preceding we obtain the following 
further examples of expansions in series. 

The function f(x) which is defined by the equation f(x) = sin(ix for 
— n < x < 7c can be expanded in the series 

2sin(i7t/ sins 2sin2a 3sin3z \ 

/(*) = sinp; = — {jpZTp ~ j^Y* + il^T 2 +•••)■ 

If we put x=- and use the relation sin(irc = 2 sin— cos—, this 
gives us the resolution of the secant into partial fractions, that is, of 
the function ; this expansion is 

COStl - 

2 

* • (-l)"(2v-l) 

jr sec nx = = 4 i 



= co8tux %_i4a?-(2v- 1)»' 

where for (J./2 we have written r. 

* This formula is particularly interesting because it shows directly that 

the function sin irx vanishes at the points x = 0, ±1, ±2 In this respect 

it corresponds to the factorization of a polynomial when its zeros are known. 



are 



446 FOURIER SERIES [Chap. 

The series for the hyperbolic functions cosh \xx and sinh iix(—n<x<n) 

cosh ( x :B =^sinh ! x TC /'J___^^, + ^^__£?^ + _ ^ 
t \2(i a [i 2 + 1* ^ + 2 2 ^+32 ' " 7' 

sinh^=2 sinh(Jt7r ('_iiE^_i sin l^ + i sin ^_ + \ 



EXAMPLES 

1. Find the Fourier expansions for the functions which are periodic 
with period 2n and which in— iz <x^tz axe defined by the formulae 

(a) e ax . (6) (a* — ti 2 ) 2 . (c) sinox;(l + cos*). 

(d) f(x)=l(a^x^b), f(x) = 0(—n:<x<a), f(x) = 0(b <x^ jt). 

2. The function /(«) is periodic with period 1, and inOgi<l it is 

given by /(*) = <. Prove that /(«)--- - S !E^f. 

2 -re n =i » 

3. The polynomials S n (t) (Bernoulli polynomials) are defined by the 

relations: (a) £,(t) = t - J; (6) £„'(*) = raB,,^); (c) /"^-(i) * = 0. 
Find £,(<), B s (t), B t (t). J 

(Note.— The numbers B n (0) are rational, and are, in fact, the same as 

Bernoulli's numbers B n ; cf. pp. 422, 423.) 

4. Verify the Fourier expansions for the Bernoulli polynomials: 

B l{ t) = _i { £ ****** B s (t) = A ( S «n2^n 

tc U-i raj 2tc 3 l„_i n* f 

BS) = \ { £ S?5^}. B 4 (|, = - 8 { £ °a^\ 

5. Prove that S i=-, S I = H-. 

»-i re 2 6 „-! ra 4 90 

6. Prove that I_I+I-I + _...=V 

I s 3 3 5 3 7 3 32 

7. Prove that (a) 1 + 1 + — +l+...= 7 ^. 

32 ^ 5 2 72 8 

/7.X 1 ^ p 1 1 1 I* 

( 6 ) 1 -22 + 32-ii+--'=i2- 

( 6 ) 1-1+1-1+.. . = Z^. 
2* 3 4 4 4 720 

8. Obtain the infinite product for the cosine from the relation 

sin2rca; 

costm;= — : . 

2 sin7ce 



IX] CONVERGENCE OF FOURIER SERIES 447 

5. The Convergence of Fourier Series 

We now proceed to establish rigorously the theorems which 
were stated in § 3 (p. 439) and illustrated in § 4 (p. 440). 

1. The Convergence of the Fourier Series of a Sectionally 
Smooth Function. 
We first recall that if /(«) is any function which is denned 
and sectionally continuous (that is, continuous except for a 
finite number of jump discontinuities at most) in the interval 
— it ^ x 5S 77, we can form the Fourier coefficients of f(x) accord- 
ing to the formulas 

1 r + * 1 r + " 

a v = - / f(t) cos vtdt, b v = - / f(t) sinvtdt, 

and we can formally write down the series 

CO 

\a -f 2 (a y cos vx + b„ sin vx). 

This series is called the Fourier series corresponding to f(x), 
irrespective of whether it converges or not. We are now about 
to find the conditions which must be imposed on f(x) in order 
to ensure that the Fourier series corresponding to f(x) does con- 
verge and does represent f(x). We assume that f(x) is extended 
periodically beyond the interval — it <.x^tt. 

The theorem which we shall now prove is as follows: 
If the function f (x) is sectionally smooth * and at each point of 
discontinuity (x) satisfies the equation f (x) = £ { f (x — 0) -f f (x + 0) }, 
then the Fourier series corresponding to f (x) converges at every point 
and represents the function. 

To prove this theorem we consider the partial sums 

n 

S n {x) = |a + 2 (a„ cos vx + 6„sin vx). 

If for the coefficients we substitute the integral expressions 
found above and then interchange the order of integration and 
summation we obtain 

S n (x) = — I fit) ; + 2 (cos vt cos vx -f sin vt %m.vx) [ dt, 

* That is, f(x) is sectionally continuous and its derivative /'(a;) is sectionally 
continuous also. 



448 FOURIER SERIES [Chap. 

or, using the addition theorem for the cosine, 

SJx) = - f + f(t) \l + Xcoav(t- x)\ dt. 

If we now apply the summation formula obtained on p. 436, this 
becomes 

2tt j -„ smf(,J — x) 

Finally, making the transformation t = (t — x) and noting the 
periodicity of the integrand, we obtain 

sjx) =z- f( x + T ) — • T dr - 

XttJ—v sinfi 

Starting with this form of the partial sum S n (x) we can 
prove, by means of the following lemma, that S n (x) tends 
to f(x). 

Lemma. If the function s (x) is sectionally continuous in the 
interval a :£ x ^ b, then the integral 

<J> 



1= f s(t)smXtdt 



tends to as A increases. 

In the proof we may take s(x) to be continuous in the 
whole interval, since otherwise we need only carry out the 
argument for each sub-interval in which s(x) is continuous. 

As in the similar argument on p. 418 et sea., we notice 
that if A is positive the function sin M is alternately positive and 
negative in successive intervals of length 77/ A. For large values of 
A the contributions to the integral from adjacent intervals almost 
cancel one another, since on account of continuity the values of 
s(x) in two such adjacent intervals differ from one another only 
slightly. We make use of this circumstance by transforming the 
integral I by the substitution t= r -\- h, where h = 7r/A; then 
sinAf= — sin At, and we obtain 



J~b-h 
s(r -f- h) sin At dr. 



' s\ 

J a-h 

If we again write the letter t instead of t and then add the two 



IX] CONVERGENCE OF FOURIER SERIES 449 

expressions for I, we have 

2/ = — fs (t + h) sin tidt + f ~{s(t) — s(t + h)} sin Xldt 

J a-h J a 

r b 
+ s{t)smXtdt. 

J b-h 

If M is an upper bound for the absolute value of s(x), that is, 
if for all values of a; in the interval under consideration | s(x) | 
^ M, then from this expression for I the inequality 

2 I 1 1 ^ 2Mh + f ]s(t) — s(t + h) I dt 

follows at once. Now let e be any positive number; if we choose 
A so large that in the whole interval a ^ t 5S b — h the expres- 
sion I s(t) — s(t + h) I remains less than e/(6 — a) and also 

Mh = < -, then 1 1 1 < e; and consequently,* since e can 

A 2 

be chosen as small as we please, lim 1=0. 

Besides this lemma we need the integration formula 

Jo 2sin£t 2 

which is true for every positive integer n. This we readily estab- 
lish by using our summation formula for the cosine, since 

r sin(m + A) t ,. f w .. . " ,. ,, w 
/ — i — z/ ■ dt = / (A + 2 cos vt) dt = -. 
•A) 2sin^ Jo V2 ^ x ' 2 

Proo/ of the Main Theorem. — By means of the lemma it 
is easy to prove our main theorem, i.e. to prove the formula 

lim S n (x) = lim 1 f + 'f( x + t) ain(n . + * ) * dt = /(*). 



M— >-oo Z7T 



2 sin^f 



* If we assume that s(x), besides being continuous, has a sectionally con- 
tinuous derivative «'(»), the proof of this lemma follows simply on integration 
by parts. For 

js(t) sinAi* - i js(o) cosAo - «(6) cosA6+ J «'(<) oosAtdf j. 
Here we see at once that as A increases the right-hand side tends to zero. 



450 FOURIER SERIES [Chap. 

We begin by subdividing the interval of integration at the 
origin. For fixed values of x the function * 

2 sin^ 

is sectionally continuous in the interval j£ t ;g it. For this is 
obvious when < t ^ 77, while the continuity when t = follows 
from the assumed existence of the right-hand derivative 

lim /(*+*)-/(»+<>) _ lim /(»+*)-/(»+ 0) # 2aJnj< 
i->o, «>o < i-*-+o 2sin£< ' £ 

-lim /(* + <)-/(*+<» 
«-»-+o 2 sin^f 

Hence, as A = w -f \ increases, the integral 

1 r" 

- / s(t) sin M it 

77 ■'0 

1 f ti , ^sinAi^ 1 r*,, , „ 4 sinAi , 
= ^- / /(*+*) -^— r- dt — — I fix 4- — — eft 

tends to zero. 

Since, however, the factor f(x 4- 0) can be taken out of the 

second integral on the right, and since for A = n 4- £ the integral 

f" sinAi , . . J 77 . ,.,,., 

_/ . , «f is equal to -, we immediately obtam the equation f 

lun 9 - f'f(x +t)^dt= I f(x + 0). 
x-^„277- / o sin# 2 

In the same way we obtain 

lim * /° /(* + <) ^S& =£/(*- 0), 

x->oo2tt-'-» smff 2 

for the interval —rr^Lt^O, and by addition 
x-*-» 277 J -" sinji 

* For this notation see p. 439. 

fBy putting x — 0,f(t) = (sin i«)/' in this equation, and then replacing i 
by k/A, we obtain the important relation (of. pp. 251-253) 



x-+«J u 2 



IX] CONVERGENCE OF FOURIER SERIES 45 * 

2. Further Investigation of the Convergence. 

In the neighbourhood of those points where the function f(x) 
is discontinuous the Fourier series does not converge uniformly; 
for according to Chap. VIII, § 4 (p. 393), a uniformly convergent 
series of continuous functions possesses a continuous sum. Never- 
theless, we have the following important theorem: 

If a sectionally smooth periodic function has no discontinuities, 
its Fourier series converges absolutely and uniformly. The conver- 
gence of the Fourier series for any sectionally smooth function what- 
ever is uniform in every closed interval which contains no point 
of discontinuity of the function. 

In order to prove this theorem we start from a fundamental 
inequality satisfied by the Fourier coefficients of any function 
f(x) which is sectionally continuous (note that f(x) is not assumed 
to be sectionally smooth). This so-called Bessel's inequality states 
that for all values of n 

I V 4- £ (a* + b*) 2£ - J + \f{x)fdx. 

The proof follows from the fact that the expression 

\ f( x ) ~ h a o — ^ (a v cos vx + b sin vx) \ dx 
— <- „=.i J 

is always positive or zero. If we evaluate the integral by 
expanding the bracket under the integral sign and recalling the 
orthogonality relations and the definitions of the Fourier 
coefficients, we at once obtain Bessel's inequality in the form 

f^{f{x)Ydx- *\L* + i(a* + b y *)} ^ 0. 

In addition to Bessel's inequality we make use of Schwarz's 
inequality (p. 13): if u^, w 2 , . . . , u n and v±, u 2 , . . . , v n are 
arbitrary real numbers, it is always true that 



(Jes- 9 -)' 



l 2 w„ 2 . 2 v*, 

v=l v=l 



the sign of equality occurring only when the sequence u is pro- 
portional to the sequence v. 

We now assume that the periodic function f(x) is sectionally 
smooth, and also continuous. The derivative g(x)=f'(x) is 



452 FOURIER SERIES [Chap. 

sectionally continuous, and we easily show that c„ and d r , the 
Fourier coefficients of g(x), satisfy the relations 

c = 0, 

for on integration by parts we have 

1 r + " 
c„ = — / g(x) cos vx dx 

= - f( x ) cos vX \ + - / /(*) sin vx <£b = v&„, 

77 I — it 77 ./— it 

a similar proof holding for the other statements. 

Bessel's inequality applied to the function g(x) therefore 
gives us 

S *(<** + K 2 ) = S (c, 2 + <i 2 ) ^ - f +T {g(x)Ydx. 
v=i v=i ir J -* 

If for brevity we denote the right-hand side of this inequality 
by M 2 , and apply Schwarz's inequality, we find that when m> n 

m m 

S | a„ cos vx -|- fc„ sin vx | ig £ \/(a r 2 + fe„ 2 ) 

since -\/( a * 2 + K 2 ) * a tne amplitude of the periodic function 
a„ cosvx + 6„ sinvx. 

00 J 

But owing to the convergence of S — the right-hand side, 

v=.l v a 

which is independent of x, can be made as small as we please by 
choosing n and m large enough, which proves the absolute and 
uniform convergence of the series.* 

In order to prove the above theorem for sectionally smooth 
functions which are discontinuous, we first consider a special 
function ip{x) of this type. 

* The same considerations show incidentally that for periodic functions 
with continuous derivatives of the (ft — l)-th order and derivatives of the 

n 

A-th order which are at least sectionally continuous, the sum Sv^a,,* + 6„*) 

remains below a fixed bound. This gives us a definite statement about the 
order to which the Fourier coefficients vanish. For such a function the Fourier 
series of the derivatives up to the order (ft - 1) converge absolutely and uniformly. 



IX] CONVERGENCE OF FOURIER SERIES 453 

In the interval — it < x < 77 we define i/i(x) as equal to x; out- 
side this interval t/i(x) is extended periodically. According to 
p. 440 its Fourier series is 

„ /sina; sin2a; sin 3a; \ 

2 V^ 2~ + "l — + 'T 

This series cannot be uniformly convergent, for its sum is 
the discontinuous function ifi(x). We shall show, however, 
that the convergence is uniform in every interval — I ^x^l 
for which < I < -n. 

The proof is based on a special artifice.* We observe that in 

the interval — I < x <L I the function cos - is never less than the 

~ ~l 2 

positive quantity cos - = k. If we multiply the absolute value 

of the difference between the »»-th and ra-th partial sums of the 
above series (m > n), that is, the expression 

\S m (x)-S n (x)\ 



= 2 



sin(w+l)a; sin(w+2)a; , sin mx\ 

— -j . . . ~r 

n -f 1 w-(- 2 m \ 



by the function cos -, then in accordance with the well-known 

trigonometric formula 2 sin to cosv = sin(w -\- v) + sin(w — v), we 
obtain the absolute value of the expression 

x isin(w + l)a; sin(w -\- 2)x sinma;) 

£i COS — { — - r~ — • • • *t~ — } 

2 \ n+ 1 n+ 2 ~ mx l 

__ sin(w-f |)a; sin(w+|)a; , sin(m-f|)a; 

m+1 w+2 °" — m 

sin (n -f- 1) a; _ sin (w -f- 1) a; sin(w+f)a; , 

n+ 1 m+2 w+3 ~~ +•••• 



* We are led to this artifice naturally by observing that the function 2y cosy, 

when extended periodically beyond the interval —~^y^~, remains con- 

2 2 

tinuous, so that according to the first part of the theorem its Fourier series 
must converge uniformly and must represent the function. This series, however, 
is obtained if we multiply the Fourier series for 2y by cosy. If we now put 
y — xj2, this multiplication leads to the steps in the text. 



454 FOURIER SERIES [Chap. 

If we combine the terms on the right which have the same 
numerators, we obtain the expression 

sin(n + |)a; sin(m + \)x 
n + 1 — m 

, sin(w+|)a; sin(w+f)a; sin (to— i)a; 

(n+l)(n+2) (n + 2) (n + 3) + '"~ t ~ (to-I)to ' 

and since cos - ^> k and | sinw | ^ 1, we obtain the estimate 
\S m {x)-S n (x)\ 

/cLw+1 to (w -f 1) (ra + 2) (to — 1)toJ 

But the expression on the right does not depend on x, and in 

00 1 

virtue of the convergence of the series S it can be made 

v =iv{v-\- 1) 

as small as we please by choosing n and to large enough. This 
implies the uniform convergence of the Fourier series, which we 
asserted. 

Now that we have obtained the expansion for a particular 
discontinuous function, we can (cf. p. 441) transfer the discon- 
tinuity to any arbitrary point in the interval by translation of 
the curve or of the co-ordinate system. In fact, the function 

^(r -g) — o/ 8 " 1 ^— ^) _ sm2(x — g) | sin3(a;-g) | \ 

is continuous except at the points (2k + l)n + i, where k is an 
integer. On passing these points, however, the function jumps 
by an amount — 2-rr, from the value 77 to the value — tt, while at 
these points themselves the value of the function is zero. 

If now f(x) is any sectionally smooth function which in the 
interval — 77 ^ x ;S 77 is discontinuous only at the points 
£i> $2' • • • » £™> an( i ^ on passing these points from left to right 
the function jumps by the amounts S 1; 8 2 , . . . , S m respectively, 
then the function 

/(*)+ h 0(* + w - &) + h ,/,(*+ tt- fo + . . . 
In Ztt 



IX] CONVERGENCE OF FOURIER SERIES 455 

will be continuous and sectionally smooth, and hence by the 
previous proof can be expanded in a uniformly convergent Fourier 
series. We now obtain the Fourier series of the function /(x) by 
adding the finite number of Fourier series corresponding to the 

functions —_!,/, (a; +7r—^), .... — ^t/,{x+ir— g m ) term by 

term. Our theorem is thus proved. 

This result is quite adequate for most mathematical investi- 
gations and for applications. We would, however, point out 
that the investigation of Fourier series has been pushed much 
further. The conditions for expansion in Fourier series which 
we have found here are sufficient, but by no means necessary. Func- 
tions with far fewer continuity properties than those discussed 
here can be represented by Fourier series. There is an extensive 
literature devoted to these questions and to the general problem 
of the expansibility of a function in a Fourier series. As a 
remarkable result of such investigations we mention the fact 
that there are continuous functions whose Fourier series do not 
converge in any interval, no matter how small. Such a result 
does not in any way impugn the usefulness of Fourier series; 
on the contrary, it must be regarded as evidence that the con- 
cept of a continuous function involves fairly complicated possi- 
bilities, as has already been shown by the example of continuous 
functions which nowhere have a derivative. 



Appendix to Chapter IX 

Integration of Fourier Series 

One of the remarkable properties of Fourier series is their 
term-by-term integrability. In general, a series can be integrated 
term by term if it is uniformly convergent; otherwise term-by- 
term integration may lead to false results. In contrast with this, 
for Fourier series, we have the theorem: 

If f(x) is sectionally continuous in — ti 5S x ^ -n, and if the 
series £a + 2(a„ cosx-(- b„ sinx) is the Fourier series corresponding 
to f(x), then this series can be integrated term by term between any 



456 FOURIER SERIES [Chap. IX 

two limits £ and x lying in the interval — it :£ x £S tt; in symbols, 

J f(x)dx=J \a dx-\-~Ll\ a v cosvxdx-\- 1 b„sm.vxdx 1. 

Moreover, for every fixed value of £ the series on the right converges 
uniformly in x. The remarkable feature of this theorem is that 
not only do we not require that the Fourier series for f(x) shall be 
uniformly convergent, but we need not even assume that it 
converges at all. 

To prove this, let the function F(x) be denned by the equation 

{f(x) — $a }dx. This function is sectionally smooth, 

and by the definition of a we have F(tt) = F(—tt) = 0, so that 
F(x) can be extended periodically and continuously. The Fourier 

00 

series \A + S {A v cosvx + £„ sinvx) of the function F(x) there- 

fore converges uniformly to F(x). We now investigate the co- 
efficients A v and B v . By integration by parts as on p. 449, we 
find that, for v > 0, A p = — bjv and B„ = ajv. Hence for any 
values £ and x in the interval — tt ^ x ^ tt, we have 

00 

F(x) — F(£) = S {A v (cos vx — cos v£) + B v (sin vx — sin v£) } 

v = l 

= Z j — " (sin vx — sin v£) —-- (cos vx — cos v|) }, 

converging uniformly in x. If we replace F(x) by its definition, 
this becomes 

/ f{x)dx — %a fdx = S (a r I cos vxdx-\- 6„ / sin vxdx), 

which was to be proved. 

It is easy to see that if f(x) is periodic and sectionally con- 
tinuous the term-by-term integration can be performed over any 
interval whatever. 



CHAPTER X 

A Sketch of the Theory of Functions 
of Several Variables 

Up to this point we have concerned ourselves exclusively 
with functions of a single independent variable. We must now 
go on to consider functions of several independent variables. 
Even the applications of the calculus force us to take this step. 
In almost all the relationships which occur in nature, in fact, the 
functions in question do not depend on a single independent 
variable; on the contrary, the dependent variable is usually 
determined by two, three, or more independent variables. Thus, 
for example, the volume of an ideal gas is a function of a single 
variable, the pressure, if we keep the temperature constant, but 
not otherwise. As a rule the temperature also varies, and the 
volume depends upon a pair of values, namely, the value of the 
pressure and that of the temperature; it is therefore a function 
of two independent variables. 

From the point of view of pure mathematics also, the need 
for detailed study of functions of several independent variables 
is urgent. Here we shall be able to take advantage of what we 
have previously learned, so that in many cases we have only to 
make simple extensions of our arguments. 

It is usually sufficient to consider the case of only two inde- 
pendent variables x and y, so long as no essentially new con- 
siderations are required for an extension to functions of three or 
more variables. In order to keep our statements and notation 
simple, therefore, we shall consider only two independent 
variables as a rule. 

A systematic presentation of the differential and integral 
calculus for functions of several variables is impossible within 
the compass of this volume, but will be given in Vol. II 



458 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

of this treatise. All that can be done here is to give the reader 
a preliminary view of some of the most important new concepts 
and operations. We shall frequently rely on intuitive plausi- 
bility, the full proofs being developed subsequently in Vol. II. 



1. The Concept op Function in the Case op Several 
Variables 

1. Functions and their Ranges of Definition. 

Equations of the form 
u = x 2 + y 2 , u= x — y, u= xy, or u = -\/(l — x 2 — y z ) 

assign a functional value u to each pair of values (x, y). In the 
first three of our examples this correspondence holds for every 
system of values (x, y), while in the last case the correspondence 
has a meaning only for those pairs of values (a;, y) for which the 
inequality as 2 + y 2 :gj 1 is true. 

In these cases we say that u is a function of the independent 
variables x and y. This expression we use in general whenever 
some law assigns a value of u as dependent variable, corre- 
sponding to each pair of values (x, y) belonging to a certain 
specified set. The relation between x, y and u may be stated in 
terms of a "functional equation", as above, or by means of a ver- 
bal description such as "u is the area of the rectangle with sides 
x and y ", or it may follow from physical observations, as, for in- 
stance, in the case of the magnetic declination for different lati- 
tudes and longitudes. The essential thing is that a correspondence 
exists. Similarly, u is said to be a function of the three inde- 
pendent variables x, y, z if for each triad of values (x, y, z) of a 
certain set there exists a corresponding value of u given by some 
definite law; and similarly for the general case of functions of n 
independent variables %, x 2 , . . . , x n . 

The set of values which the pair (x, y) can assume is called 
the range of definition of the function u =f(x, y). For the pur- 
poses of this chapter we shall restrict our attention to the sim- 
plest types of range of definition. We shall consider that (a;, y) 
is limited either to a so-called rectangular region (domain) 

a iS*x<Lb, c fS y <>d, 



X] FUNCTIONS OF SEVERAL VARIABLES 459 

or else to a circle determined by an inequality of the form 
(a; — af + (y — b) 2 S «*• 

In the case of functions of three variables x, y, z we shall again 
consider only rectangular regions 

a 5£ a; <1 6, c^y^d, e 5S z S/ 

and spherical regions 

(a; — a) 2 + (y — bf + (z — cf ^ r 2 . 

In dealing with more than three independent variables geometri- 
cal intuition fails us, but it is often convenient to extend geo- 
metrical phraseology to this case also. Thus for functions of n 
variables x 1> . . . , x„ we shall consider regions 

<h ^ *\ ^ b v a 2 <; x % <; 6 2 , . . . , a„ ^ x„ <: b n 

and also regions 

(x 1 -a 1 ) 2 +(x 2 -a 2 ) 2 + ... + (x n -a n ) 2 ^r\ 

which we call rectangular regions and spherical regions respec- 
tively. 

2. The Simplest Types of Functions. 

Just as in the case of functions of one variable, the simplest 
functions are the rational integral Junctions or polynomials. 
The most general polynomial of the first degree (linear function) 
is of the form 

u = ax -f- by + c, 

where a, b, and c are constants. The general polynomial of the 
second degree has the form 

u s= ax 2 + bxy -\- cy 2 -\- dx -\- ey +/. 

The general polynomial is a sum of terms of the form a mn x m y n , 
where the quantities a mn are arbitrary constants. 

Rational fractional functions are quotients of polynomials; 
to this class belongs e.g. the linear fractional function 

u= ga; + ty+o 
a'x + b'y + c'* 



4<5o FUNCTIONS OF SEVERAL VARIABLES [Chap. 

By extraction of roots we pass from the rational functions to 
certain algebraic functions,* e.g. 

In the construction of more complicated functions of several 
variables we almost always fall back on the well-known functions 
of one variable; f e.g. 

w = sin (xy) or u = log (y 2 + cos %x). 

3. Geometrical Representation of Functions. 

Just as we represent functions of one variable by means of 
curves, we seek to represent functions of two variables geometri- 
cally by means of surfaces; henceforward we shall consider only 
those functions which can actually be represented in this way. 
We achieve this representation very simply by considering a 
rectangular co-ordinate system in space, with co-ordinates x, 
y, and u, and marking off above each point (x, y) of the range 
(R) of definition of the function the point P with the third 
co-ordinate u — f(x, y). As the point (x, y) ranges over the region 
R the point P describes a surface in space. This surface we take 
as the geometrical representation of the function. 

Conversely, in analytical geometry surfaces in space are 
represented by functions of two variables, so that between such 
surfaces and functions of two variables there is a reciprocal 
relation. 

For example, to the function 

u = V(l - x 2 — y») 

there corresponds the hemisphere lying above the x, y plane, with unit 
radius and centre at the origin. To the function u = x 2 -f- y 3 there corre- 
sponds a so-called paraboloid of revolution, obtained by rotating the para- 
bola u = x 3 about the M-axis (fig. 1). To the functions u = x 3 — y 3 and 
« = xy there correspond hyperbolic paraboloids (fig. 2). The linear function 
u = ax + by + c has for its graph a plane in space, f 

* For an accurate definition of the term " algebraic function " see p. 485. 

f Cf. also the section on compound functions (p. 472). 

J If in the function « — f(x, y) one of the independent variables, say y, 
does not occur, so that u depends on x only, say « = 9(x), the function is 
represented in xyu-sp&ce by a cylindrical surface obtained by erecting the 
perpendiculars to the uz-plane at the points of the curve u — g(x). 



X] 



FUNCTIONS OF SEVERAL VARIABLES 



461 



This representation by means of rectangular co-ordinates 
has, however, two disadvantages. Firstly, intuition fails us 
whenever we have to deal with three or more independent vari- 
ables. Secondly, even in the case of two independent variables it 
is often more convenient to confine the discussion to the xy- 
plane alone, since in the plane we can sketch and make geometrical 
constructions without difficulty. From this point of view another 
geometrical representation of the function, by means of contow 
lines, is to be preferred. In the ay-plane we take all the points 
for which u=f(x, y) has a constant value, say u—k. These 





Fig. 1. — u = *' + y* 



Fig. a. — u= x* — y* 



points will usually lie on a curve or curves, the so-called contour 
line for the given constant value of the function. We can also 
obtain these curves by cutting the surface u=J(x, y) by the 
plane u = k parallel to the ay-plane and projecting the curves 
of intersection perpendicularly on to the tcy-plane. The system 
of these contour lines, marked with the corresponding values \, 
k 2 , . . . of the height k, gives us a representation of the function. 
As a rule k is assigned values in arithmetic progression, say 
k = vh, where v = 1, 2, . . . . The distance between the contour 
lines then gives us a measure of the steepness of the surface 
m = /(•£, y); for between every two neighbouring lines the value 
of the function changes by the same amount. Where the contour 
lines are close together the function rises or falls steeply; where 
the lines are far apart the surface is flattish. This is the principle 



462 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

on which contour maps such as those of the Ordnance Survey 
and the U.S. Geological Survey are constructed. 

In this method the linear function u = ax-\-by + cJB represented by 
a system of parallel straight lines ax + by + c = k. The function u = a; 2 + y 2 
is represented by a system of concentric circles (cf. fig. 3). The function 
u = x 2 — y 2 , whose surface has a saddle point at the origin (fig. 2) is re- 
presented by the system of hyperbolas shown in fig. 4. 

The method of representing the function u = f(x, y) by con- 
tour lines has the advantage of being capable of extension to 
functions of three independent variables also. Instead of the 




Fig. 3. — Contour lines of u *= x* + y* 



Fig. 4. — Contour lines of u «■ x* — y* 



contour lines we then have the level surfaces f(x, y, z) = k, where 
k is a constant to which we can assign any suitable sequence 
of values. For example, the level surfaces for the function 
u = x 2 + y % -f- z 2 are concentric spheres about the origin of the 
co-ordinate system. 



Example 

1. For each of the following functions sketch the contour lines corre- 
sponding to z = — 2, — 1, 0, 1, 2, 3: 

(a) z = x*y. (d) z = y*. 

(6) t = x* + y 2 - 1. / ^ x 

(c) z = z 2 - y\ (e) * V \ & + y 2 / 



X] CONTINUITY 463 

2. Continuity 
1. Definition. 

As in the case of functions of one variable, the basic require- 
ment that functions should be capable of being represented 
geometrically leads to the analytic condition of continuity. Here 
again the concept of continuity is given by the following de- 
finition: a function u = f(x, y), defined in a region R, is said to 
be continuous at a point ($, 77) of R if for all points (x, y) near 
(£, 7}) the value of the function f(x, y) differs but little from i(£, ■??), 
the difference being arbitrarily small if only (x, y) is near enough 

to (€, v). 

More precisely: the function i(x, y), defined in the region R, 
is continuous at the point (£, ij) o/R, provided that for every posi- 
tive number e it is possible to find a positive distance 8 = 8(e) 
(in general depending on e and tending to with e) such that for all 
points of the region whose distance from (£, tj) is less than 8 
(that is, for which the inequality 

(^-a 2 +(y-^) 2 ^s 2 

holds) the relation 

\f(*,y)-Mr,)\^ e 

is satisfied. Or, in other words, the relation 

\f(i+h,r,+ k)-f(i,r,)\^ e 

is to hold for all pairs of values (h, k) such that F+Pg § 2 
and (i+ h,7] + k) belongs to the region R. 

If a function is continuous at every point of a region R, 
we say that it is continuous in R. 

In the definition of continuity we can replace the distance 
condition A 2 + Jfc* ^ 8 2 by the following equivalent condition: 

To every e > there shall correspond two positive numbers 
8 t and S 2 such that 

l/(f +*»!»+*)-/«, ij)|^e 
whenever | h | ^ S 2 and | k | ^ 8 2 . 

The two conditions are equivalent. For if the original con- 
dition is fulfilled, so is the second if we take 8 X = 8 2 = 8j-y/2; 



464 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

and conversely, if the second condition is fulfilled so is the first, 
if for 8 we take the smaller of the two numbers S x and 8 2 . 

The following facts are almost obvious: 

The sum, difference, and product of continuous functions are 
also continuous. The quotient of continuous functions is continuous 
except where the denominator vanishes. Continuous functions of 
continuous functions are themselves continuous (cf . the note on 
pp. 473-474). In particular, all polynomials are continuous, and 
all rational fractional functions are also continuous except where 
the denominator vanishes* 

2. Examples of Discontinuities. 

In the case of functions of one variable we met with three 
kinds of discontinuities: infinite discontinuities, jump discon- 
tinuities, and discontinuities at which no limit is approached 
from one side or both. With functions of two or more variables 
no such simple classification is possible. In particular, the situa- 
tion is made more complicated by the fact that discontinuities 
may occur not merely at isolated points but also along whole 
curves. 

Thus for the function u = the line x = y is a line of infinite 

x — y 
discontinuity. As we approach the line from one side or the other the 
values of u increase numerically beyond all bounds through positive or 

through negative values. The function u = has the same line of 

(x — yf 

discontinuity but tends to +00 as we approach the line from either side. 

The function u = has the single point of discontinuity x = 0, 

<* a + y 2 1 

v = 0. The function u = sin — , tends to no limit as we approach 

" V(a; 2 + y 2 ) 

the origin; the surface which it represents is obtained by rotating the 

graph of the function u = sin - about the u-axis. 

Another instructive example of a discontinuous function is given by 

the rational function u = — ^— . In the first instance the function is 
& + y a 

* Another obvious fact, which, however, is worth stating, is as follows: 
•/ a function f(x, y) is continuous in a region R and is different from zero at an 
interior point P of the region, it is possible to mark off about P a neighbourhood, 
say a circle, belonging entirely to ~R, in which f(x, y) is nowhere equal to zero. 
For if the value of the function at P is a, we can mark oft about P a circle so 
small that the value of the function within the circle differs from a by less than 
o/2, and therefore is certainly not zero. 



X] CONTINUITY 465 

undefined at x = 0, y = 0, and we supplement the definition by assuming 
that «(0, 0) = 0. This function has a peculiar type of discontinuity at the 
origin. If we put x = 0, that is, if we move along the y-axis, the function 
becomes «(0, y) = 0, which has the constant value for all values of y. 
Along the a-axis we likewise have u{x, 0) = 0. Thus at the origin the 
function u{x, y) is continuous in a; if we keep y at the constant value and is 
continuous in y if we keep x at the constant value 0. Nevertheless, the 
function is discontinuous when considered as a function of the two vari- 
ables x and y. For at every point of the line y = x we find that w = 1, 
so that arbitrarily near the origin we can find points at which u assumes 
the value 1. The function is therefore discontinuous at the origin,* and 
cannot be defined at the origin in such a way as to make it continuous. 

The above example shows that a function can be continuous 
in x for every fixed value of y and continuous in y for every fixed 
value of x and yet discontinuous when considered as a function 
of the two variables. The essential point in the definition of con- 
tinuity is that the value of the function at a point P must be 
arbitrarily close to the value of the function at a point Q, provided 
only that Q is near enough to P; it is not permissible to restrict 
the position of Q relative to P in any other way. 



Examples 

x 2 4- V 

1. Examine the continuity of the function 2 = - ^___„i_^. Sketch the 

Vx* + ]p 
level lines z = k (&= — 4, — 2, 0, 2, 4). Exhibit (on one graph) the 
behaviour of z as a function of x alone for y = — 2, — 1, 0, 1, 2. Similarly, 
exhibit the behaviour of z as a function of y alone for x = 0, ±1, ±2. 
Finally, exhibit the behaviour of z as a function of r alone when is con- 
stant (r, 6 being polar co-ordinates). 

2. Show that the following functions are continuous: 

(a) sin (a? + y). . x 3 + y 3 

... ataxy a? + y* 

W + / (d) 3? log(** + s,»). 

* More generally, on the straight line y — x tan a inclined at the angle o to 
the z-axis we have u — 2 tano/(l + tan 2 a) — 2 sin a cos a -= sin 2a. The sur- 
face corresponding to the function u — 2xyftx* + y*) is therefore formed by 
rotating a straight line at right angles to the w-axis about that axis until it 
coincides with the x-axis, and simultaneously raising or lowering it so that the 
height sin 2a is associated with the angle a. As a increases up to 45° the 
straight line rises to the height 1, and subsequently falls to the level of the 
y-axis and below it to the depth 1, thereafter rising again to the level of the 
a;-axis. The surface enveloped by the moving straight line is known as the 
cylindroid; it is of importance in mechanics. 

16 (K798) 



466 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

3. Find whether or not the following functions are continuous, and 
if not, where they are discontinuous: 



(a) sin?. 
x 



(b) 



** + y* 

x*+y*' 



(C 



x* + y* 



(d) 



3? + y* 
x* + y' 



3. The Derivatives of a Function of Several 
Variables 

1. Definition. Geometrical Representation. 

If in a function of several variables we assign definite numerical 
values to all but one of the variables and allow only that one 
variable, say x, to vary, the function becomes a function of one 





Fig s 



Fig. 6 



Sections of « = /(*, y) 



variable. We consider e.g. a function u = f(x, y) of the two 
variables x and y and give y a definite fixed value y = y = c. 
The function u = f(x, y ) of the single variable x which is thus 
formed may be simply represented geometrically by letting the 
surface u = f(x, y) be cut by the plane y = y (cf. figs. 5 and 6). 
The curve of intersection thus formed in the plane is represented 
by the equation u=f(x, y ). If we differentiate this function in 
the usual way at the point x = x (we assume that the derivative 
exists), we obtain the partial derivative of f(x, y) with respect to 
x at the point (x , y ). According to the usual definition of the 
derivative this is the limit * 

iim /( x o + ^ y )— /(% y ) _ 



* If (x„, y ) is a point on the houndary of the region of definition we make 
the restriction that in the passage to the limit the point (x + h, y„) must always 
remain in the region. 



X] PARTIAL DERIVATIVES 4^7 

Geometrically this partial derivative denotes the tangent of the angle 
between a parallel to the x-axis and the tangent line to the curve u = f(x, y ). 
It is therefore the slope of the surface u = f(x, y) in the direction of the 
x-axis. 

To represent these partial derivatives several different nota- 
tions are used, of which we mention the following: 

iim f( x o + h >y<>)-f(*o,y ) =fx(Xot yo) = UxiXoj yo) . 

If we wish to emphasize that the partial derivative is the limit 
of a difference quotient we denote it by 

iT or a - /* 

ox ox 

Here we use a special round letter 3, instead of the ordinary d 
used in the differentiation of functions of one variable, in order 
to show that we are dealing with a function of several variables 
and differentiating with respect to one of them. 

It is sometimes convenient to use Cauchy's symbol D, men- 
tioned on p. 90, and write 

ox 

but we shall seldom use this symbol. 

In exactly the same way we define the partial derivative of 
f(x, y) with respect to y at the point (x , y ) by the relation 

Km /(*o,yo + *)-/(*o,yo) =M y ) = d l = D v f(x , y ). 
*-»o k oy 

This represents the slope of the curve of intersection of the sur- 
face u=f(x, y) with the plane x=x perpendicular to the 
jo-axis. 

Let us now think of the point (x , y ), hitherto considered 
fixed, as variable, and accordingly omit the suffixes 0. In other 
words, we think of the differentiation as carried out at any point 
(x, y) of the region of definition of f(x, y). Then the two deri- 
vatives are themselves functions of x and y: 

««(*> V) =/.(*, V) «= d -^P^ and u v (x, y) =f y (x, y) = d J^dl m 
ox oy 



468 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

For example, the function u = x* -f y a has the partial derivatives 
u x = 2x (in differentiating with respect to x the term y 2 is regarded as a 
constant and so has the derivative 0) and «„ = 2y. The partial derivatives 
of u — x?y are u x = Zx*y and u v = x 3 . 

We similarly make the following definition for any number 
(n) of independent variables 
df(x 1 , x 2 , . . . , x„) 
dx 1 
_ hm f(xi +h,x 2 , . . . , x„) —J(x x , a; 2 , . . . , x n ) 



*->0 



h 



= fxS X l' X » • • • ' *») = D xJ(^ X 2> ■ • • > *»)> 

it being assumed that the limit exists. 

Of course we can also form higher partial derivatives of f(x, y) 
by again differentiating the partial derivatives of the "first 
order ",f x (x, y) and/„(a;, y), with respect to one of the variables, 
and repeating this process. We indicate the order of differen- 
tiation by the order of the suffixes or by the order of the symbols 
dx and dy in the " denominator ", from right to left,* and use 
the following symbols for the second partial derivatives: 

3 (df\_dj = =Z)2 . 

3 /9/\_ *f -f =Z) 2 f 
dx\dy/ ox ay 

d (df\_ dj , =Di f 

dy\ox/ oyax 

8y \3y/ By 2 
We likewise denote the third partial derivatives by 



di\d*)~ W~ Jxx " 

o hy\ _ a 3 / = f 



9 / dj \ = 
dx \dxdyj 



3 3 / _, 

' — J X. 



dx z dy 

• In Continental usage, on the other hand, g- f J J is written ^-J- . 



X] PARTIAL DERIVATIVES 469 

and in general the n-th derivatives by 

9 /9"-y\ 3*/ 

3a; Xdx"- 1 ) dx n Jx ' 

3 /3»-y\ 

3«/\3a; n_1 / dydx n ~ 






Finally, we shall study a few examples of the actual calcu- 
lation of partial derivatives. According to the definition all the 
independent variables are to be kept constant except the one 
with respect to which we are differentiating. We therefore have 
merely to regard the other variables as constants and carry out 
the differentiation according to the rules by which we differen- 
tiate functions of a single independent variable. 

Thus for example we have: 

1. Function f(x, y) — xy; 
first derivatives, f x = y, f v = x; 

second derivatives, f^ =0, f XB = f vx = 1, / w = 0. 

2. Function f(x, y) = V(x 2 + y a ); 

first derivatives, f x = * — -, /„ = ■- y — -. 

V(x 2 +y 2 ) V(x 2 + y % ) 

(Thus for the radius vector r = V(x i + y 2 ) from the origin to the point 
(a;, y) the partial derivatives with respect to x and to y are given by the 
cosine, cos<p = x/r, and the sine, simp = y/r, of the angle <p, which the 
radius vector makes with the positive direction of the x-axis.) 

Second derivatives, 

V(x* + y*) 



, _ V(x 2 + y 2 ) 

J xx ~~ 



J xv Jyx 



x 2 +y 2 



xy 



V(x* + y 2 f 

V(** + J/ 2 ) - . f 
f _ V{x 2 + y 2 ) 



y* 


sin 2 9 


V(x 2 + y 2 f 


r ' 


sin 9 cos 9 




r 




x> 


cos 2 9 


V(x 2 + y 2 f 


r 



47° FUNCTIONS OF SEVERAL VARIABLES [Chap. 

3. Reciprocal of the radius vector in three dimensions: 

1 1 



f(x, y, z) == 



V(a^ + y* + z 2 ) r ' 
first derivatives, 



V(a; a + y* + z 2 ) 3 r 3 ' 

f = y = _y 

" V(a^ + y a + z 2 ) 8 r 3 ' 

8 V(a; a + y* + z 2 ) 3 r 3 ' 

second derivatives, 

f =-1 + ™ f - - 1 + W f - 1 , 3z» 

/ = f _ 3x V f _ * _ 3yz , _ , _ 3zx 
Jxv Jvx -ft Jvz — Jzv ~S~> Jzx — Jxz £"• 

From this we see that for the function / = - the 

equation V (* + »» + *) 

Jxx ~ Jmi \ Jzz — ~i T ; — V 

r 3 r 5 

holds for all values of x, y, z except 0, 0, 0; as we say, the equation 

Jxx i Jyy + Jzz = 

is satisfied identically in x, y, z by the function f(x, y, z) = 1/r. 

4. Function f(x, y) = -i- e - ( JC_a ) , ' 4 J'; 

VJ 
first derivatives, 

second derivatives, 

f = C 3 i_ _ 3 im# + <* - «) 4> \ e -(,- a) .,*v 



X] PARTIAL DERIVATIVES 471 

The equation 

fxx - Sv = 
is therefore satisfied identically in x and y. 

Just as in the case of one independent variable, the possession 
of derivatives is a special property * of a function. All the same, 
this property is possessed by all functions of practical impor- 
tance, except perhaps at isolated exceptional points. 

In contrast with functions of one variable, the possession of 
derivatives does not imply the continuity of the function. This 

is clearly shown by the example u = i— already considered 

x*+y* 

on pp. 464-465; for the partial derivatives exist everywhere, 
and yet the function is discontinuous at the origin. But, as is 
stated by the following theorem, the possession of bounded 
derivatives does imply continuity: 

If a function f(x, y) has partial derivatives f, and fy everywhere 
in a region R, and these derivatives everywhere satisfy the in- 
equalities 

\Mx,y)\<M, \f v {x,y)\<M, 

where M is independent of x and y, then f (x, y) is continuous every- 
where in R. 

In particular, if f x and/ s are continuous they are necessarily 
bounded, so that f(x, y) is also continuous. 

The proof of this theorem we shall leave for Vol. II. 

The reader will have noticed that in all our examples the 
equation f xv =f vx is satisfied. In other words, it made no dif- 
ference whether we differentiated first with respect to x and then 
with respect to y or vice versa. This is no accidental occurrence. 
In fact, we have the following theorem: 

If the " mixed " partial derivatives t^ and t^ of a function 
f (x, y) are continuous in a region R, then the equation 

Jvx == J XV 

holds everywhere in the interior of this region; that is, the order 
of differentiation with respect to x and y is immaterial. 

* The expression " differentiable " implies more than that the partial deri- 
vatives with respect to x and to y exist. Cf . Vol. II. 



472 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

By applying this theorem to f x and f„, then to f xx , f xy , f yy , 
and so on, we find that 

Jxxv Jxvx Jyxxy 
Jxyy == Jvxv == Jvyxt 
Jxxvv ^ Jxyxy === Jxwx ^ = Jvxxy ^ Jyxyx == Jyyxxi &C., 

and in general we have the following result: 

In repeated differentiation of a function of two variables the 
order of differentiation can be changed arbitrarily, provided only 
that the derivatives in question are continuous functions. 

For the proof of this theorem we refer the reader to Vol. II. 

Examples 

1. Find the first partial derivatives of the following: 

(a) vte + t,*. (d) * . 

V(l + x + y* + z 2 ) 

(b) sin(a^ — y). (e)ysin(xz). 

(c) e*~y. (/ ) log V(l + *» + «/ a ). 

2. Find all the first and second partial derivatives of the following: 

(a) xy. (d) x". 

(6) log as/. (e) e(**). 

(c) tan (arc tana; + arc tany). 

3.* Find a function f(x, y) which is a function of (x* + y 2 ) and is also 
a product of the form ty(x)ty{y); that is, solve the equations 

f(x, y) = ^(3? + y 2 ) = 4t{x)4/{y\ 

for the unknown functions. 



4. The Chain Rule and the Differentiation of Inverse 

Functions 

1. Functions of Functions (Compound Functions). 

It often happens that a function u of the independent 
variables x, y is stated in the form 

u=f(£,-n, ...), 

where the arguments £, -n, . . . of the function / are themselves 
functions of x and y: 

t = 4>(x, y), ij = jj(x, y), ... . 



X] THE CHAIN RULE 473 

We then say that 

w =/(£ v> ■ • ■) =f(<f>( x > y)> 4>( x > y)> • • •) = F i x > y) 

is given as a compound function of x and y. 
For example, the function 

u = e*'y(x + yf 

may be written as a compound function by means of the relations 
u = <£ 7) 3 = /(5, 7]); % = x*y, 7) = x + y. 

Similarly, the function 

u = log(a; + 1) . arc cos V(4 — x 2 — y*) 
can be expressed in the form 

u = 7) arc cos 5 = /(£, yj); £ = V(4 — a? — j/ 2 ), 7) = log(* + 1). 

In order to make this concept more precise, we assume to 
begin with that the functions $ = <f>{x, y), tj = ^(x, y), . . . are 
defined in a certain region R of the independent variables a;, y. Then 
to every point (x, y) of R there corresponds a point (£, ij, . . .) 
in the space with co-ordinates g, 17, . . . . As the point (x, y) 
ranges over R, the point (£, 77, . . .) will range over a certain 
set of values. We assume that the point (f, 77, . . .) always lies 
within a region S in which /(£, ■>?,...) is denned. The function 
u = f(<f>{ x > y)> #"i V)> • • ■) = F(x, y) is then defined in the region 
R. 

Referring to our examples, in the first we find that 5 and 7) are denned 
for every x, y and/(£, 7)) is defined for every 5, vj, so that our region B can 
be taken to be the whole xy-pkme. In the second example, however, the 
region S is restricted by the inequality | ? | £? 1, since for | 5 I > I the 
function arc cos £ is undefined. Secondly, the region B is restricted by the 
inequalities x + 1 > and x 2 + y 2 fg 4, since for other values \ and tj 
are not both defined. Thirdly, the region R must be further limited by the 
inequality 3 g x 2 + V* in order that the point with co-ordinates 5, t) 
shall fall in 8; that is, the restriction [ Z, [ ^ 1 implies that x 2 + y 2 ;> 3. 
Hence B consists of the part of the ring 3 5S x 2 -\- y 2 ^ 4 lying to the right 
of the line x = — 1. 

The following theorem on compound functions is an im- 
mediate consequence of the definitions: 

If the function u = 1(£ , tj, . . .) is continuous in S and the 
functions £ = <f>(x, y), tj = i/i(x, y), . . . are continuous in E, then 

16* IE 798) 



474 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

the compound function u = F(x, y) is continuous in R. The reader 
will be able to prove this for himself. 

2. The Chain Rule. 

We now turn our attention to compound functions of the 
type u=f(g, 7], . . .), where £, •>?, ... depend on the single 
variable x: 

€ = tfr), V = <M»), 

For such functions we have the important theorem known as 
the chain rule: 

If the function u = f(£, tj, . . .) has continuous partial deri- 
vatives of the first order in S, and the functions £ = <f>(x), i) = </r(x), 
. . . have continuous first derivatives in the interval R, a ^ x 5S b, 
then u = f {<j>{x), ^r(x), . . .} = F(x) has a continuous derivative in 

R, and 

F'(x)=f l i'(x)+f vV '(x)+.... 

The right-hand side of this equation is an abbreviation for 

/*{#*), #*),...}*'(«)+.... 

To simplify the notation we shall assume that /is a function 
of the three arguments £, 77, £. We shall denote by x Q an arbi- 
trary fixed point of the interval a ^ x ^ b, by £ , tj , £ 
the corresponding values & = <f>(x ), -q = ifi(x ), £ = x (x ), 
and by £, ij, £ the values <f>(x), i/i(x), %(x) corresponding to a 
variable point x = x -f A. We first write down the identity 

*(*) - *■(**) 

= /(£» i?» £) — /(&> *?o> £0) 

In each bracket on the right we observe that only one of the 
independent variables changes its value. Hence to each bracket 
we can apply the mean value theorem for functions of one variable, 
and obtain 

F{x) - F(x ) 

= (£- lo) Ml % 0+ (v- Vo)L (£0, v> Q+(t- W/< (U v , 0> 



X] THE CHAIN RULE 475 

where | lies between £ and $, -rj between rj and -q, and £ between 
6 and £. Further, by the mean value theorem, we have 

£ — £ = <f,(x) - <£(x ) = (a: — a; ) f fo), 

*l — Vo= <A(») — 'I'M = (a — a ) "A'^), 

C - Co = Xfc) — x(«%) = (* — afe) X^s). 

where a^, x 2 , and x 3 all lie between x and a;. Substituting these 

values in the last equation and dividing by x — x , we have 

F(x) - F(x ) 

X Xq 

We now let x tend to x . Owing to the continuity of (f>(x), if>(x), 
X(x) the quantities |, 17, £ tend to £ , ij , £ respectively, and a 
fortiori f, ij, £ do likewise. Also x 1 , x 2 , and x 3 tend to % 
Since all the functions on the right are continuous, we have 

]hQ F M -JW = r{Xo) 

=/f(£o> %. WfW+/,(^ Vo, ?o)fW+/;(?o. %. Co) x'K), 

thus establishing the formula for F'(x). 

The continuity of F'(x) follows immediately from the formula, 
since <£', if/', and x' » re continuous by hypothesis and / f , /,, and 
f i are continuous functions of continuous functions. 

This theorem may be extended to compound functions of 
two or more variables, as follows: 

If the function u = f(£, ij, . . .) has continuous partial deri- 
vatives of the first order in the region S, and the functions (;= <f>(x., y), 

rj = tfi{x, y), have continuous partial derivatives of the first order 

in R, then u = F(x, y) = i{<f>(x, y), ifi(x, y), . . .}has continuous 
partial derivatives of the first order in It, and these derivatives are 
given by the formulas, 

f* = i ' t *.+J ;<a* + — 

Fy=f(<f>y+fr l 4>v + 
These formulae are often written in the abbreviated form 
u x = u ( £ x + M,1J a + . . . , 
m v = m 4 |, + «,i7«+ • • • • 



476 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

To establish them we temporarily introduce the notation 
g(x) = <f>(x, y ), h(x) = ifi(x, y ), . . . , where y is a fixed value 
of y. By the definition of the partial derivatives it follows that 
g'(x) = <f> x (x, y ), h'(x) = ifi x (x, y ), .... Similarly, if we write 
H(x) = F(x, y ), we have H'(x) = F x (x, y ). We now apply the 
theorem just proved to the function u = H(x) =/(!, r), . . .) 
= /{g(x), h(x), . . .}, and obtain 

H'(x ) =ft 9 '(x ) +f,h'(x ) +... . 

Returning to the original symbols, we have 

-Fsfoo Vo) =/^*( a; o> Vo) +f v >Px(xo> y ) + • • • • 
The other formula is proved in a similar way. 

If we wish to calculate the derivatives of higher order we need 
only differentiate the right-hand side of our formulae again with 
respect to x and y, regarding f it /,,... as compound functions. 
Thus for u = /(& 7]) =f{<f>(x, y), <j,(x, y)}, we have 

u xx =f(S <f>x 2 + 2/f, <f> x lfi x +/„„ </> x 2 +/( 4>xx +/, <A*S, 

u xv =/« <f>x <f>y +/|, (<f>x>Pv+ 4>v >Px) +fm 'I'x $v +/f fxv +/, <l>xv, 

««» =/« ( t>v 2 + Vir, 4>n <t>v +f m <A» 2 +ft <t>vv +/, <l>vv 

3. Examples.* 

1. u = e xt!M y+y coax . 

Here we put £ = x tanj/, in = y cosa;, bo that SL = tany, L. = . 

oos 2 y 

r) x = — y sins, y]„ = cosx. Since u = e£ +T >, uj = m, = «f +i, ttiid 

Ujt _ e x tany+y cosx ( tan ^ _ y sm X ) t 

„ _ ^cVmy+ycasx(_^__ + CO sa;). 
\cos 2 2/ / 

2. An example of a compound function of a single variable is 

u ={<?(*) }**>= 5" = /(5,v]), 
where we put 5 = g(x), i\ = h(x). We immediately obtain 

^ = ft V + /,tf = ^~ 1 5' + 5" ^g I ■ V 

= fo (*) }**> f *(*) ^ + *'(*) logg(x) } . 
I g(x) ) 

We have already dealt with a special case of this by rather artificial methods 
(p. 203). 

* We would emphasize that the following differentiations can also bo carried 
out directly, without using the chain rule. 



X] THE CHAIN RULE 477 



4. Change of the Independent Variables. 

A particularly important type of compound function occurs 
in the process of changing the independent variables. For ex- 
ample, let u = /(£, 13) be a function of f and rj, which we interpret 
as rectangular co-ordinates in the l^-plane. If we rotate the 
axes in the |rj-plane through an angle 6 we obtain a new system 
of co-ordinates x, y, related to the co-ordinates £, ij by the 
equations: 

£ = SCCOS0 — ysin0, ij = zsinfl-f y cosfl, 

or x = |cos0 + rjam.0, y= — £sin0+ ij cos0. 

The function u = /(£, yj) can then be expressed as a function of 
the new variables x, y: 

u=f(Z,- n ) = F{x,y). 

Then the chain rule immediately gives 

u x = u ( cos0 + m, 8in.6, w„ = — w f sin0 + u v cosO. 

Thus the partial derivatives are transformed by the same formulae 
as the independent variables. This is true for rotation of the 
axes in space also. 

Another important type of change of co-ordinates is the change 
from rectangular co-ordinates x, y to polar co-ordinates r, 8. 
This is done by means of the equations 

x=rcoad, y = rsind, 

r = a/(x* + y% 6 = arc tan y ~. 

x 

We then find that for an arbitrary function u=f(x, y) with 
continuous partial derivatives of the first order we have 

« =/(z, y) =f(r costf, r sinfl) = F(r, 6), 

a x V a sm ^ 

u x — u r r x + ufl x = u r - — u e 2- = u r cost) — u e , 

r r* r 

n V , £ • a 1 cos ^ 

u v = u r r y + u e y — u r z + u e — = u r sine/ -f- u e . 

r r r 



478 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

From this we obtain the equation 



«« 2 +W» 2 =Mr 2 + i«»«. 



1 

r 2 



which is often useful. 

In general, let us consider a pair of functions £ — <f>(x, y), 
■q = i/j{x, y) which are continuous and have continuous deri- 
vatives in a region R of the ay-plane. To each point (po, y) in R 
these equations assign a point £ = <f>(x, y), rj = ip(x, y) in the 
^ij-plane. As (x, y) ranges over R, the corresponding point 
(|, rj) will range over some set of values S in the fq-plane. It is 
of course possible that several distinct points (x, y) will give the 
same values for |, 17, so that to several points (x, y) there corre- 
sponds only one point (£, rj). We shall assume that this is not the 
case, but instead that to one point Q{£, rj) in S there corresponds 
exactly one point P{x, y) in R. We may therefore look at the 
correspondence from either point of view — saying that Q cor- 
responds to P or that P corresponds to Q. The latter point of 
view can be expressed thus: to each point (£, rj) in S there cor- 
responds one x and one y, namely, the co-ordinates of P, or, in 
equations, there are two functions x = g{£, rj), y=h(£, rj), 
denned in S, which represent the correspondence inverse to 
$=$(x, y), rj= iP(x, y). 

It often happens that the functions g (£, rj), h(£,rj) are by no 
means easy to calculate, even when they do exist. Hence we 
shall now find how to obtain the partial derivatives g t , g v , h ( , A, 
directly from the partial derivatives <f> x , <f> v , ift x , ip y , without cal- 
culating g and h themselves at all. For this purpose we observe 
that if we choose any point Q($, rj), find the corresponding point 
P{g(S, rj), h(i, r])} in R, and then find the point in S correspond- 
ing to P, which is <f>{g(£, rj), h(£, rj)}, ${g(£, rj), h(£, v )}, we 
have simply returned to the point Q. That is, the equations 

f= <f>{9(£> V)> h(£> V)}> V = H9(£> V)> *(£ V)} are identities 
in £ and ij. We now differentiate * both sides of both equations 
with respect to £ and to rj. We have 

1 = 4>xfft + <i>v h, = c/> x g v + <f> v \, 

= fafft + iMf. 1 = <Px9 v + 4>vK 

* If an equation expresses an identical relationship, differentiation with 
respect to any independent variable in it yields an identity, as follows im- 
mediately from the definition. 



v 



XJ THE CHAIN RULE 

Solving these equations, we find that 

„ _ fa „ _ _ fa j. fa i _ fa 

9t ~~D' 3 * D' f— ~D' 



D' 



or 



D' ~ v 



I' 
D' 



Xe =^, x.= -^. y t =-H, y,= ^, 



5? 01 = ^ x 

D' 



where by D we mean the determinant 



D= ixVv— iyVx = 



d£ 


d£ 


dx 


dy 


dr) 
dx 


dr) 
dy 



479 



which we assume is not zero. 

This determinant D, called the functional determinant or 
Jacobian of (f, r?) with respect to (x, y), occurs so frequently that 
a special symbol is often used for it: 



Z> = 



_3(£l) 



d(x, y)' 



Examples 

1. Calculate the partial derivatives of the first order for: 
1 



(«)/- 



(C) /= x 2 + y log (1 + x* + J/ a + z 2 ). 



V(x 2 + ^ 2 + 2xy cosz) 

(6) /= arc sin — 5—. (<Z) / = arc tan V (x + yz). 

z + y 2 

2. Calculate the derivatives of (a) / = x^\ (6) / = (( \ J . 

3. Prove that if J(x, y) satisfies " Laplace's equation " 

8a? dy* 
does <p(x, «)=/( -, — - — _). 

4. Prove that the functions 

(«) /(«. ») = log vV + y ! ). (6) g(x, y, z) = y (g , ^ + ^ . 

(c) A(x, i/, z, w>) = , 

X 2 + «/ 2 -+- Z a + U! 2 



480 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

satisfy the respective Laplace's equations: 

(«) fxx + fw = °- ( 6 ) 9xx + SW + S,i = 0. 

(c) h xx + h yv + h zll + h ww = 0. 

5. Given z= r 2 cos 6, where r and 6 are polar co-ordinates, find z x 
and z„ at the point 6 = - , r = 2. 

Express z r and z e in terms of z x and z„. 

6. By the transformation %= a -{- ax -\- py, i] = 6 — fix + «y> in 
which a, 6, a, p are constants and a 2 + p 2 = 1, the function m(k, y) is 
transformed into a function {/(£, tj) of ? and tj. Prove that 

7. Find the Jacobians of the following transformations: 

(a) %=ax-{-by, i) = ex + dy; (6) r = V(a; 2 -f y 2 ), 6 = arc tan"; 
(c) ? = 3?, 1) = y 2 . 

8. If x = a;(w, »), y = y(«, «) and «=«( 5, ■»)),»= f(5, v))> prove that 

8(s, y) _ 6 (a:, y) 6 (it, u) 
8(5,7)) 8(«,»)'S(5,yi)" 

0. As a corollary to Ex. 8, prove that 

8(x, y) _ 1 

d(u, v) d(u, v) 
8(x, y) 

10. Using Ex. 9, find the Jacobians of the transformations which are 
the inverses of those in Ex. 7. 



5. Implicit Functions 

In the study of functions of several variables we have as yet 
had no analogue to the inverse function. We can regard the 
inverse function of y = f(x) as the function obtained if we 
solve the equation y — f{x)=0 for x. In this section we 
shall seek more generally to solve equations F(x, y) = for 
x or for y, and to discuss functions of several variables in a 
corresponding way. 

Even in elementary analytical geometry curves are frequently 
represented, not by equations y = f(x) or x = <j> (y), but by an 
equation involving x and y in the form F(x, y) = 0. For example, 



XJ IMPLICIT FUNCTIONS 481 

«J*2 a.2 

we have the circle x 2 + w 2 — 1 = 0, the ellipse — + y — — 1 = 0, 

a 2 b 2 

and the lemniscate (cc 2 -f- y 2 ) 2 — 2a 2 (x 2 — y 2 ) = 0. In order to 

obtain y as a function of x, or a; as a function of y, we must solve 

the equation for y or for x. We then say that the function 

V — f( x ) or a; = <f>(y) found in this way is denned implicitly by 

the equation F(x, y) = 0, and that the solution of this equation 

gives us the function explicitly. In the examples cited and in 

many others the solution can be carried out and the solutions 

stated explicitly in terms of the elementary functions. In other 

cases the solution can be obtained in terms of an infinite series 

or other limiting process; that is, we can approximate to the 

solution y =f(%) or x = <j>(y) as closely as we desire. 

For many purposes, however, it is more convenient to base 
our discussion on the implicit definition F(x, y) = 0, instead of 
resorting to an exact or approximate solution of the equation. 

The idea that every function F (x, y) yields a function 
y=f(x) or x= <f>(y) given implicitly by means of the equation 
F(x, y) = is erroneous. On the contrary, it is easy to give 
examples of functions F(x, y) which, when equated to zero, 
permit of no solution in terms of functions of one variable. Thus 
for example the equation x 2 -\- y 2 = is satisfied by the single 
pair of values x = 0, y = only, while the equation x 2 -\- y 2 + 1 = 
is satisfied by no (real) values at all. It is therefore necessary to 
investigate the matter more closely in order to find out whether an 
equation F{x, y) = can actually be solved, and what properties 
the solution has. Such an investigation we cannot undertake in 
detail here, but content ourselves with a geometrical interpre- 
tation which suggests the required results, the rigorous proofs 
being left for Volume II. 

1. Geometrical Interpretation of Implicit Functions. 

To discuss this problem geometrically we represent the 
function u = F(x, y) by a surface in three-dimensional space. 
Finding values (a;, y) which satisfy the equation ^(a;, y) = is 
the same thing as finding values (x, y) which satisfy two equations 
F(x, y) = u, u = 0; in other words, we wish to find the inter- 
section of the surface u = F(x, y) and the plane u = 0, which is 
the a;y-plane. We then suppose that we have a definite point 
{ x o> Vo) which satisfies the equation F(x , y ) = 0; that is, at 



482 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

( x o> Vo) * ne surface u = F(x, y) has a point in common with the 
plane u = 0. (If no such point exists, there is no intersection, 
and the equation F(x, y) = cannot be solved.) If the tangent 
plane to the surface u = F(x, y) at the point (x , y ) is not hori- 
zontal, it cuts the plane u = in a single straight line. Intuition 
then tells us that the surface u = F(x, y), lying near the tangent 
plane, likewise cuts the plane u = in a single well-defined 
curve. How far this curve extends does not at present concern 
us. The tangent plane will be horizontal if the two curves 
m = F(x , y) and u = F(x, y ) both have horizontal tangent 
lines at (x , y ); that is, if F x (x , y ) = and F v (x , y ) = 0. 
Thus if either F x (x , y ) 4= or F v (x , y ) #= the tangent plane 
is not horizontal, and, as we have just seen, we may expect that 
a solution in the form y—f(x) or x = <£(*/) will exist. 

If, on the other hand, both F x {x , y ) and F„(x , y ) have the 
value 0, we readily see that there is no guarantee that the solu- 
tion is possible. 

For example, f or F = 1 — V(l — a 2 — j/ 2 ) the corresponding spherical 
surface u = 1 — V(l — a? — y 2 ) has the point (0, 0) in common with the 
ay-plane. The partial derivatives F x (0, 0) and ^,,(0, 0) are both zero; 
and we find that no point other than (0, 0) satisfies the equation F — 0. 
For the function F(x, y) = xy we find that F(0, 0) = 0, while ^(0, 0) 
= F v (0, 0) = 0. Here all the points on the jc-axis and all the points on 
the y-axia satisfy the equation F(x, y) = 0; and in the neighbourhood of 
the origin we have no unique solution x = <p(y) or y = f(x). Thus we see 
that when F x (x , y ) — F y (x Q , y ) = we cannot be sure that a solution 
exists. 

If we accordingly return to the case in which one of the partial 
derivatives — say F v (x , y ), to be specific — is not zero, the graphi- 
cal suggestion that a smooth surface should be cut by a non- 
tangent plane in a smooth curve leads us to suspect that the 
following theorem is true: 

If the function F(x, y) has continuous derivatives F x and F 
and if at the point (x , y ) the equation F(x , y ) = is satisfied, 
while F y (x , y ) is not zero, then we can mark off about the point 
(xo. y<>) a rectangle x x 5S x ^ x 2 , y x ^ y 5S y 2 such that for every 
x in the interval x x 5S x :gj x 2 the equation F(x, y) = determines 
just one value y = f(x) lying in the interval y x <S y <S y 2 . This 
function y = f(x) satisfies the equation y = f (xj, and the equation 

F{x,f(x)}=0 



XI IMPLICIT FUNCTIONS 4§3 

is satisfied for every x in the interval. Moreover, the function 
y = f(x) is continuous and has a continuous derivative. 

This can actually be rigorously proved, and will be proved 
in Vol. II. Assuming it to be true, we can add the following: 

The derivative of the function y = f(x) is given by the equation 

y>=f {x )=- F * 

This follows immediately by using the chain rule. For 

i F{x,f(x)}^F x ^+F v ^=F x + FJ'. But since F{x,f(x)} 

is identically zero, its derivative is also zero; hence F x -\-F v f'= 0, 
and the formula is established. 

If we regard the right-hand side of the formula as a 
compound function of x and differentiate according to the chain 
rule, replacing y' by —FJF V , we have 

v >. = _ F V (F XX + F m y') - F X (F XV + F m y') 
V F v * 

_ _ FxxFy 2 — ^FxyF x F y -\- F yy F x 2 
F 8 

Continuing the process, we may calculate y'", y iv , &c. 

By using this formula we can usually find the derivative of a 
function given in implicit form much more easily than by solving 
first and then differentiating. 

For example, for the circle 

F (x, y) = a* + y* - 1 = 

we have y" = x = . 

f* y 

This is easily verified. For on solving the equation of the circle for y we 
obtain two solutions, namely, y=V{l — x 2 ) and y = — V(l — x i ), giving 
the upper and lower semicircles respectively. For the upper we have 



" V(l - 3?) 

for the lower «' = -, — — . 

* V(l - **/ 

so that in either case y' = . 



484 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

As another example, we have F(x, y) = e x+ y + y — x = 0. We find 
that F x ( -, — -J = 0, while F y ( -, — - J = 2. Thus the equation has a solu- 
tion y = f(x); but the actual explicit calculation of the function f(x) 
would not be simple. Nevertheless, we have 

' = _ z? = _ e * +y - 1 

y F y = e*+y + 1 

In order that the function f(x) may have a maximum or a minimum we 
must have y' = 0, that is, e x +y —1 = 0, whence y = —x. Substitution 

of y = — x in the equation F(x, y) = gives I — 2x = 0, whence x = -, 

ll 2 

3/ = If we calculate /"(x) for x = -, we find it to be negative, so that 

— -is the maximum value of y. 

An extension of this theorem for implicit functions to func- 
tions of a greater number of independent variables readily sug- 
gests itself. The extension is as follows: 

Let F(x, y, . . . , z, u) be a continuous function of the indepen- 
dent variables x, y, . . . , z, u with continuous partial derivatives 
F x , F y , . . . , F z , F u . For the system of values (x , y , . . . , z , u„) 
let F(xo, y , . . . , z , u„) = and F u (Xo, y , . . . , z , «o) # 0. 
Then we can mark off an interval u x ^ u :S u 2 about Uq and a region 
B. containing (x„, y , . . . , z ) such that for every (x, y, . . . , z) in R 
the equation F(x, y, . . . , z, u) = is satisfied by just one value of u 
in the interval u x :|S u ^ Ug. TAis wihte 0/ u, which we denote by 
u = f (x, y, . . . , z), is a continuous function of x, y, . . . , z and 
possesses continuous partial derivatives f,, f y , . . . , f z , and 

w o ~J\ x o> Vo' • • • > z o)- 
TAe derivatives of i are given by the equations 
F x + F u f x =0, 
F y + F u f v = 0, 



F.+ Fuf. = 0- 



For the proof of the existence and continuity of u we again 
refer the reader to Vol. II. The formulae for f xv , &c, follow im- 
mediately from the chain rule. 

Incidentally, the concept of an implicit function enables us 
to give a general definition of the term " algebraic function ", 



X] IMPLICIT FUNCTIONS 485 

We say that u =f(x, y, . . . ,z) is an algebraic function of the 
independent variables x, y, . . . , z if u can be denned implicitly 
by an equation F(x, y, . . . , z, u) = 0, where F is a polynomial 
in x, y, . . . , z, u; that is, if u satisfies an " algebraic equation". 
Functions which do not satisfy any algebraic equation are called 
transcendental (p. 24). 

As an example of our differentiation formula we consider the ellipsoid 

a 2 o 2 c 2 
For the partial derivatives we have 

_2x c 2 c' x 

a 2 2u a 2 u 

= _ 1y c 2 c* y m 

Uy ft 2 ' 2u ~ b 2 ' u 

and by differentiating again 

c 2 1 c 2 x _ c 2 a 2 u 2 + c*x* 

a 2 u a 2 u 2 a*u 3 

c 2 x c 4 xy 

M = — _?, 

a 2 u 2 a 2 b 2 u 3 

c 2 1 c 2 y _ c 2 6 2 m 2 + c*y* 

Uyv ~ b 2 'u + V'u* Uy -~ bW 



Examples 

1. Prove that the following equations have unique solutions for y 
near the points indicated: 



(a) x 2 + xy + y 2 = 7 


(2, 1). 


(6) x cosxy = 


('•?• 


(c) xy + logxy = 1 


(1, 1). 


(rf) z 6 + y 6 + xy = 3 


(1, 1). 



2. Find the first derivatives of the solutions in Ex. 1. 

3. Find the second derivatives of the solutions in Ex. 1. 

4. Find the maximum and minimum values of the function y = f(r) 
defined by the equation x 2 + xy + y 2 = 27. 

5. Show that the equation x + y + z = sinas/u can be solved for z 
near (0, 0, 0). Find the partial derivatives of the solution. 



*86 



FUNCTIONS OF SEVERAL VARIABLES [Chap. 



6. Multiple and Repeated Integrals 

1. Multiple Integrals. 

We consider a function u = f(x, y) which is denned and 
continuous in a rectangle R(a f^x^Lb, c ^ y 5S d), and which 
takes positive values only. We wish to assign a volume to 
the portion of three-dimensional space bounded by the rectangle 
R, the surface w=/(a;, y), and the four planes x= a, x=b, 
y = c, y = d perpendicular to the xy-plane. Moreover, the 
volume should be denned so as to satisfy certain elementary 
conditions: (1) if the three-dimensional region is a prism — 
i.e. if the function u is a constant k — the volume should be 
the product of the base by the altitude, V = (b — a) (d — c)k; 



/SST~~^y 


\ [^Tr^/j 


i A \A V A / 


V v*,v / V 



Fig. 7 

(2) if we divide the rectangle R into smaller rectangles R^ and R 2 
by drawing straight lines, then the volume over R should be 
equal to the volume over R^ plus the volume over i? 2 ; (3) if the 
three-dimensional region Rj completely includes R 2 , the volume 
of R 1 should be at least as great as that of R 2 . 

These considerations lead us to a method of denning V which 
is an immediate extension of the method of denning area in 
Chap. II (p. 77 et seq.). By constructing lines parallel to the sides 
we subdivide the rectangle R into smaller rectangles R i , R 2 , . . . , 
R n , whose areas we denote by AR lt AR 2 , . . . , AR n . In each 
rectangle Rj the function has a least value m f and a greatest 
value Mj. Therefore a prism whose base is R< and whose height 
is Mj completely includes the portion of our region over R it 
while this portion of the region contains the prism with base R, 
and height m f (cf. fig. 7). We see, therefore, that the volume of 



X] MULTIPLE AND REPEATED INTEGRALS 487 

the portion in question lies between nijR, and MjR t . Thus the 
total volume V should be such that 

S mjARf ^ V ^ S M,AR t . 
-1 y-i 

Suppose now that the number n of rectangles increases 
beyond all bounds in such a way that the length of the longest 
diagonal tends to zero. Intuition leads us to expect that the two 
sums 'Zm j AR i and HMjAR, will both converge and will tend to 
the same limit. This limit we therefore call the volume V. 

The reader will have observed that we have carried out an 
immediate generalization of the discussion in Chap. II (p. 78). 
As in Chap. II, we call the common limit of the sums Swi^AE, 
and TiMjARj the integral of the function u = f(x, y) over the rect- 
angle E, and we denote it by the symbol 



fff(x,y)dr. 



It is at once clear that if in each rectangle R } we choose a point 
(£j, 7]}) and find the corresponding value of the function /(£,, ij,) 
then the limiting relation 

lim S/(& Vj )AR,= fff(x, y)dr 

must hold; for the sum 2/(&, t] } )AR } lies between l.m i AR j and 
HiMjARj, both of which approach the integral as a limit. 

As a particular method of subdividing R into smaller rect- 
angles, we may divide the side a^Lx^b into n intervals of length 
Ax = (b — a)/n and the side c 5S y ^ d into m intervals of 
length Ay— (d — c)/m, and then draw parallels to the axes 
through the points of division thus marked. The area of each 
rectangle R t is then AR, = Ax Ay. Choosing a point (g h rj f ) 
arbitrarily in each rectangle R t , we form the sum 

Z*/(6, „)AK, = S l /(f / , rjJAxAy. 

As n and m both increase without limit, this sum approaches the 
integral as a limit. This type of subdivision suggests a second 
notation for the integral, which has been in common use since 
the time of Leibnitz, namely, 



fffl x > V)dxdy. 



488 FUNCTIONS OF SEVERAL VARIABLES fCHAP. 

The proof that such a limit exists if u = f(x, y) is continuous 
can be carried out as in the appendix to Chap. II (p. 131 et seq.). 
We shall, however, assume without proof an even stronger state- 
ment, namely, the following: 

If the function f(x, y) is continuous except along a finite number 
of smooth * curves y = f (x) or x = <f>(y) along which f(x, y) has 
jump discontinuities, then the double integral 



fff(x,y)dr 



exists. 

The proof of this we leave for Vol. II. It depends essentially 
on the fact that as the number of rectangles increases the total 
area of the rectangles having points in common with the curves 
of discontinuity tends to zero. Thus even though Mj and m f 
may differ considerably for such rectangles, they give rise to 
little difference between the sums SMjARj and Em^A-fi^. 

With this assumption we can find the area under surfaces 
u = f(x, y) for which (x, y) ranges over quite complicated regions 
R. For suppose that the region R is bounded by a finite number 
of curves x = <f>(y) or y = i/j(x) with continuous derivatives, and 
that f(x, y) is continuous in R. We enclose R in a rectangle R', 
and at the points of R' which do not belong to R we assign to 

f(x, y) the value 0. Then we take the integral / I f(x, y)dr, 

taken over the region R', as the volume under the surface 
u = f(x, y), where (x, y) is in R. This integral is usually 

denoted by I ff(x, y)dr. 

Certain simple but important theorems relating to these 
double integrals follow directly from the definition. Here we 
simply state the theorems; the reader will be able to prove them 
without any trouble. 

If f (x, y) and g(x, y) are integrable over a rectangle, then so are 
f ± g> and °f » where c is a constant: 

If tf( x ' y} ±s( x > y)} dr = fff( x ' y) dr ± // 9( x > y) dr > 

ff cf(v, V)dr = cfff(x, y)dr. 
* By smooth curves we mean, as before, curves with continuous derivatives. 



XI MULTIPLE AND REPEATED INTEGRALS 489 

If f (x, y) ^ g(x, y) in R, then 

fff( x > y) dr ^ff gfr, y) dr - 

Ij R is the sum of two regions R x and R 2 , then 

f ff(x, y)dr = [f f(x, y)dr + ff f(x, y)dr. 

2. Reduction of Double Integrals to Repeated Simple Integrals. 

We now have a definition of the double integral, with its 
interpretation as a volume and with the many possibilities of 
usefulness which our experience with the single integral suggests; 
but as yet we do not possess a method for evaluating such 
integrals. In this section we shall see how the calculation of a 
double integral can be reduced to that of two single integrals. 

We suppose that u=f(x, y) is a function which is denned 
and continuous in a rectangle R, a 5S x 5S b, c ^ y ^ d. If we 
fix upon any value x in the interval a :£ x ^ b, the function 
f(x , y) is a continuous function of the remaining variable y. 
Hence the integral 

r d 

J f{x ,y)dy 

exists, and can be evaluated by the methods of earlier chapters. 
This integral has a definite value for each value of x that we may 
choose; in other words, the integral is a function <£(a; ) of the 
quantity x ; 

f c f(x,y)dy= <f>{x). 

For example, suppose that u =f(x, y) = x 2 y 3 , 5S x ^ 1, 

£S t/ ^ 3. For each fixed x in the interval fS x ^ 1 the 

x^y 3 dy can be evaluated, and is, in fact, — x 2 ; that 
is, it is a function of x. Or if f(x, y) = e xv , 1 ^ x ^ 2, 

r* 1 

1 <= w ^ 4, we have / e xv dy ■= (e ix — e x ). 

Having thus found the function <f> (x), we can prove that it is 
continuous; this is a simple consequence of the uniform con- 



490 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

tinuity of f(x, y). It is therefore possible to integrate <f> (x) betweeD 
the limits a and b, thus obtaining the " repeated integral " 

J 4(x)dx =f (j f(x, y) dyj dx. 
By reversing the order of the process, first calculating the func- 

r b 

tion of y denned by / f(x, y) dx and then integrating from c to 

J a 

d, we obtain the other repeated integral 

I e (f a f( x >y) dx ) d y- 

These integrals, as we have seen, are obtained by a double 
application of the ordinary simple integration which we have 
studied in previous chapters. Their importance lies in the 
following fact: 

For continuous functions f(x, y), and for functions f(x, y) 
having at most jump discontinuities on a finite number of smooth 
curves, the repeated integrals are equal to the double integral: 

j Ij^' y } dr = L (Ie f( x ' ^ dy ) dx 

= L [f a ^ x '^ dx ) dy - 

We shall content ourselves with an intuitive discussion of 
the case where /(cb, y) is continuous. In our original discussion of 
the double integral regarded as the volume lying above the rect- 
angle a^,x<Lb, c^y 5S <Z and below the surface u =f(x, y), 
we obtained this volume by subdividing the solid into vertical 
columns and then letting the diagonals of the bases of these 
columns approach zero. Instead of this we can divide the solid 
into slices of breadth h = {d — c)/n by drawing the lines 
y = c + vk {v = 0, 1, . . . , n) parallel to the x-axis and then 
constructing a plane perpendicular to the a^-plane through each 
Kne (cf. fig. 8). These planes cut the solid into n slices which 
grow thinner as n increases, and whose total volume is equal to 
the double integral. We now see that the volume of each slice 
is approximately (but of course not as a rule exactly) equal to 



X] MULTIPLE AND REPEATED INTEGRALS 49 1 

the product of the thickness k by the area of the left-hand face, 
that is, equal to 

r* 

k / f(x, c + vk) dx. 

J a 

Therefore, if we write , 

r b 
<t>{y) = l f{x,y)dx 

the desired volume is represented approximately by 

n-l 

S k<f>(c-\- vk). 

■— 




Fig. 8 

As n -> oo these sums tend to 

£<i>(y)dy- 

It is therefore reasonable to expect that the volume or double 
integral is exactly equal to 

f e <f> (y) dy =£ (f a f(x, y) dx) dy, 

which is the statement made above. A similar discussion makes 
it equally plausible that the statement 

! a (X -f( x > y) dy ) dx = SL ^ x ' y) dr 

is also true. 



492 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

3. Examples and Remarks. 

A few examples will serve to illustrate how this theorem may be 
used to evaluate double integrals. For the function u = f{x, y) = x*y, 
0^icgl,0^yg2,we have 

-/ 

•'O 



r-1 1 I 1 1 

2a?dx = „«* = . 
2 lo 2 



The above example belongs to a general class of functions 
whose integration is often simplified by the following theorem: 

If the function u = f(x, y), a 5£ x ^ b, c ^ y ^ d, can be 
represented as the product of a function of x alone, and a function 
of y alone, 

f(x,y)=4>{x)tj,{y), 

then the double integral of f is the product of two simple integrals: 
ff t f{x, y) dr = (J J (x) dx) (jf V (y) dy) . 

For on integration with respect to y the function <f>(x) can be 
treated as a constant and placed in front of the integral sign, while, 

on integration with respect to a, / >p(y)dy is a constant; hence 

f a \f e H*)'l> (y) dy) dx =f a \4> (x) £ tfi (y) dy) dx 

= (fj(y)dy)(fj(,x)dx). 

For the function u = sin (x + y), Oga;^ tt/2, Ss y Sa Jt/2, we 
have 

/• r /-t/2 / /.ir/2 \ 

/ / sin(a; + y)dr = ( / sin(a; + y)dy)dx 

— / ( — cosf x + -) + cosa;J dx = I (siax + cosx)dx 

IW2 
= ( — cosa; + sins) =1 + 1 = 2. 
lo 

Again, let us calculate the volume V of the vertical prism whose base 
in the zy-plane is bounded by the co-ordinate axes and the line x + y = 1, 
and which lie? below the plane u = 2x + Sy. We first extend the func- 



X] MULTIPLE AND REPEATED INTEGRALS 493 

tion u = f(x, y) to the square ^i^l.Ogygl by equating it to 
outside the triangle (the base of the prism). Then for each x in the inter- 
val the function f(x, y) is different from for ^ y ^ 1 — x only; hence 

f /(*. V)dy = f l(x, y)dy = f (L + 3y)dy 
Jo Jo Jo 

= 2s(l - x) + I (1 - x? ^ _ * + ?, 

^ F = !Ij (X > V)dT =/ 1 (- i" " « + D* " f 

The device just used is capable of extension to any function 
u = f{x, y) which is defined in a region R bounded above and 
below by curves y= ip(x) and y = <j>(x). For suppose R is de- 
fined by the inequalities a^x<^b, </>(x) <i y 5S *p(x). We mark 
off a rectangle R', a^x-^b, c<ly ^d, completely containing 
R, and outside R we put/= 0. Then 

/ /(*. y) fy = 1 , /(*» y) d y 

for every x in the interval a ^ x ^ 6, so that 

ff B /(*, */) * =/£ /(a?, «/) dr = £* (fj(x, y) dy) dx 

= J. Uiwf&'yWy)**- 

Thus to find the volume V of the ellipsoid — +^+"—1 = 

a* ft 2 c 2 ' 

we notice that -F is the volume under u — f(x, y) = c . / ( 1 — * — — Y 
2 v \ a 2 6V 

this function f(x, y) being defined only inside an ellipse 

3+S" - -»V('-3 s 'W0-S)— *■** 

Calculating the repeated integral we first have 

/ nx,y)dy=l c v( 1- 5-y* 

l ~(t, bx *\ y , cj/ //, a; 2 „2\|+»^(l-»»/a>) 
= — -c( 6 — — larc cos—, (- _2 . / [ 1 — *_ i 

2\ « 2 / V(6'-W/o') T 2Vl a 2 6«/L 6 va-«'/««) 

--|('-5)<»-")+»=?'('-S> 



494 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

Proceeding with the integration, we have 

J F -J!:(j!>'»*)*-£i*( 1 -3*-?(-»)L 

2tt 



= - cb [ - a ) 
2 \S J 



' abc, 
3 



so that V = - nabc. 

3 

4. Polar Co-ordinates. 

In our definition of the double integral, the subdivision into 
rectangles was of course chosen simply because such a subdi- 
vision is most convenient in connexion with rectangular co- 
ordinates. As we already know, however, there are many applica- 
tions in which polar co-ordinates are much more suitable than 
rectangular. If we are considering a function f(p, fa where p 
and </> are polar co-ordinates, the most convenient subdivision 
is not into rectangles, but into regions bounded by arcs of circles 
p = constant and radii j> — constant. Suppose, then, that our 
function f(p, fa is defined in such a region R, specified by the 
inequalities a^.p<Lb, a ^ <f> <* ft. (If f( p , fa is originally 
defined in a region R' not of this type, we enclose R' in a larger 
region R of the desired form and put f(p, fa = outside R'.) 
Then, just as on p. 486, we can insert points of subdivision p = a, 
Pi> P2> • • • j Pn = b, <f> = a, fa, fa, . . . , <j> m = ft and construct 
the corresponding radii and arcs of circles, thus dividing R into 
regions R {i , of area AR H . In each R ti we choose a point (p if , <f> ti ) 
and form the sum 2/(p ,<^) AR ti , and then let m and w increase 
without limit. Then the sum will again tend to the volume under 
the surface u =f(p, fa, and we may denote this by the integral 



flf(p,<p)dr. 



So far we have encountered nothing essentially new. The 
point of importance is to learn how to evaluate these integrals 
by reducing them either to repeated integrals or to integrals in 
terms of rectangular co-ordinates. For this purpose we mark 
off a pair of rectangular axes in a new plane, the p^-plane, and 
call them the />-axis and the ^-axis respectively. Correspond- 
ing to the point in R with polar co-ordinates p, <f> we plot the 



X] MULTIPLE AND REPEATED INTEGRALS 495 

point in the p^-plane with rectangular co-ordinates p, <f>. Thus 
the region R, a 5S pf^b, a^<f><L ft is represented in the 
/j^-plane by a rectangle R', a<L p^b, a <S <£ <S £, and 
each small region R i} , p t _ x <; p <S p<, <p t _^ <S <£<:<£, is represented 
by a small rectangle R i} '. But the area AR it ' of the rectangle 
R t / is not the same as the area AR i} of R t) . The relation 
between them is easily found. The area A.R*/ is simply 
(4>j ~~ <Pi-i) (.Pi — Pi-i)> while the area AR ti is given by the 
formula 

=Upi+ pi-i) {& — <t> f -i) (Pi - Pi-!) =Upt+ Pi-d&Ru'- 

In each region R ti let us now choose the point p ( = %(p t + p^, 
<f>i — i(<f>i + <f>i-i)- Then by definition 



fjnp, fldr = lim S/fo, ^kRi,. 

But 2/fo, £,)AB, = Z/fe, ^)p t Ai?,./, 

and the latter expression is just the sum which we form in de- 
fining the double integral of the function f(p, </>)p over the rect- 
angle R' in the p^-plane. Hence as the fineness of the subdivision 
increases the sum approaches this integral and 



ffj(p, <p)dr=ffj{ P> <f>)pdr'=ffj-(p, <p)pdpd<p 

= L (fj {p ' *)/"*#) ^=jf(j[/(/>> <f>)pd P y<f>. 

As an example, let us calculate the volume V of the sphere of radius a. 
The upper hemisphere is given by the equation u = V(o a — p 2 ), Ogp^o, 
g 9 S 2tt. Thus 

i r <(j:^'-*»<>>H:(-i<*-<-nh 

1 r 2 " S j 



2jta 3 
"3"' 



so that V = - 7ta 3 . 
3 



496 FUNCTIONS OF SEVERAL VARIABLES [Chap- 

/oo 
e~ x *dx. 
-00 

The formulae of the preceding sub-section enable us to calculate the 
area under the curve y = e~ **, — oo < x < oo, which frequently occurs 
in the theory of probability. This integration is especially interesting, in 
that we can evaluate the definite integral from — oo to oo of a function 
for which we cannot find a primitive function or an indefinite integral at all. 

Let us first consider the integral /„ of the function e — <*'+3 , " ) = e~ p " 
over the circle 2a p f^ a. This is given by 

7 « = r (f ■"■' ^ = rs - 1 •-*)* - mi - e ~ ai) - 

The square — o ^ x 5j a, — a £= j/ 5j a contains the circle ^ p ti a 
and is contained in the circle ^ p ^ 2a, and the integrand e~ x '~ y is 
everywhere positive; hence 

tc(1 - «-«*) = /„ g ("" (T e-*'-y'dy)dx g J 2o = jt(l - «-*"'). 
The integral can be written in the form 

f" e ~ x '( f e ~ y ' d y) dx = ( f e-*'<te) , 
hence 

rt(l — e-°") ^( f e-*'dx\ g tc(1 - e~ ia '). 

If we now let a increase without limit, this gives the equation 

e- x 'dx— Vjt, 



/: 



and our integral is evaluated. 

6. Moments and Centre of Mass; Moments of Inertia. 

In Chap. V, § 2 (p. 283) we saw that the moment of a system 
of points P ls P 2 , . . . , P„ with co-ordinates (x v yj, (x 2 , y 2 ), . . . , 
(x n , y n ) and masses m^, m 2 , . . . , m n about the z-axis is given by 

n 

£ m t yi, and that the ordinate of its centre of mass is given 

»— 1 

by the equation 

-in n 

r) = ■=--- S m„y p , where M= S m„ 
M. v =\ »=i 

with analogous expressions for the moment about the y-axis 
and the abscissa of the centre of mass. We now extend these 



X] MULTIPLE AND REPEATED INTEGRALS 497 

ideas to masses distributed uniformly over a region R. We 
suppose that a mass is distributed with density 1 over the region 
R; that is, that each portion of R with area A.R has also mass 
AjR. Then the total mass M of R is the same as the area of R, 

M= f [dr. 



-If.' 



Let us now divide R into portions R l , . . . , R„ with areas 
Ai^, . . . , AR„, and in each portion R v choose a point (£„, ij„). 
If we imagine that the total mass A2J K of the portion R v is con- 
centrated at the point (f„, tj v ), the moment of the resulting 
system of points with respect to the as-axis will be Si^AB,,, and 
the ordinate of the centre of mass will be 

Xr, v AR v = S^AR„ 
SAfl, M 

If we now let n -> 00 and let the diameter of the greatest R„ 
tend to 0, these sums tend to the integrals 



.= //**. 



V = 




respectively. These expressions we take as the definitions of the 
moment T x of R about the a;-axis and of the ordinate ij of its 
centre of mass. Similarly, the moment about the y-axis and 
the abscissa g of the centre of mass are respectively given by 

T^flxdr, eJ-lj^. where M-ff*. 

For example, the moment of the semicircle R, —p^x^p, 
£s y ^ V (p a — 3?), about the z-axis is 

and since M = I I dr= area M — - up*, 

,, (E798) 



498 FUNCTIONS OF SEVERAL VARIABLES [Chap. 

By a similar argument, starting from the definition of the 
moment of inertia I x of a system of particles, 

I x =~Lm v y*, 

we arrive at the expression for the moment of inertia of the 
region R about the o>axis, 

and similarly we obtain the moment of inertia with respect to 
the y-axis, 



II 



x 2 dr. 



Analogous formulae hold for three-dimensional regions R; 
the co-ordinates £, 17, £ of the centre of mass are given by 

fffxdr fffydr f f 7 ' zdr 

S- m ' v== M ' 4= M * 

where M = J f J \dr = volume of R. To find the moments of 

inertia l x , l y , I z of R about the x, y, z-axes respectively, we must 
remember that the distance of the point (x, y, z) from the ataxia 
is V(2/ 2 + z2 )> hence for a system of particles the moment of 
inertia about the aj-axis is Sffl»V(y, 2 + 2, 2 ) 8 = Srojy, 2 -)- a, 2 ), 
and on dividing R into sub-regions and passing to the limit as 
before we obtain the formula 

I x = fffy + z*)dr. 

Similarly Z„ = fjj (x* + z 2 ) dr, 

I z = fff B (x* + y*)dr. 

Thus the moment of inertia of the cube — h^x^h, — h<.y ^h, 
—h^z^h about the z-axis is 



I z=f_ {f (f^i^ + y^dz^dy^dx 

= f if 2ft(a~>-fy a )<fyjefe= f 2A (2*% + - hA dx 



-h yj-h ) J-h 



X] MULTIPLE AND REPEATED INTEGRALS 499 

The significance of the moment of inertia, as we have already 
remarked in Chap. V (p. 286), lies in the fact that in rotatory 
motion it plays the part taken by the mass in translatory motion. 
For example, if the region R rotates about the s-axis with angular 
velocity w, its kinetic energy is ^I x <» 2 - This, however, is not 
the only application of the concept of moment of inertia; for 
example, it is also important in structural engineering, where it 
is found that the stiffness of a beam of a given material is 
proportional to the moment of inertia of the cross-section taken 
about a line through its centre of mass. The reader will find 
further information about this in any textbook on strength of 
materials. 

7. Further Applications. 

The student should not assume that the applications already 
discussed exhaust the possibilities of the double integral. For 
instance, we have not proved the important theorem that the 
area A of the surface z=f(x, y), where {x, y) is in R, is given 
by the integral 



A 



/a i+ G9 ,+ G0> 



provided — and -^ are continuous; and we have left many other 
dx ay 

interesting fields untouched. These further developments, how- 
ever, do not come within the scope of the present book and must 
be left for Vol. II. 



Examples 



1. Perform the following integrations 


(a) f f xy(x*—y*)dydx. 
Jo Jo 


(6) / / ooa(x + y)dydx. 
Jo Jo 


c r 2 i 

(c) / / — dydx. 
J\ Ji xy 


(d) f f xe*"dydx. 
Jo Jo 



500 FUNCTIONS OF SEVERAL VARIABLES [Chap. X 



JO •'0 



Vl-x' 

y 2 dy dx. 



' / ydydx. 
•'o 

2. Find the volume between the aa/-plane and the paraboloid 
z = 2 — s 2 — y 2 . 

3. Find the volume common to the two cylinders je 2 + 2 2 = 1 and 
S/ 2 + z 2 = 1. 

4. By integration, find the volume of the smaller of the two portions 
into which a sphere of radius r is cut by a plane whose perpendicular dis- 
tance from the centre is h ( < r). 

6. For the following figures find the area, the centre of gravity, the 
moments about the x- and t/-axes, and the moments of inertia about the 
x- and y-axes: 

(o) the semicircle ^ y ^ V(r 2 — x 2 ); 

(b) the rectangle gi^o, ^y f^b; 

(c) the rectangle — a ^i^n, — 6 ^ y :£ 6; 

(d) the ellipse | y | ^ 6 ^^1 - 5|); 

(e) the triangle with vertices (0, 0), (a, 0), (0, 6): 

6. For the following figures find the volume, the centre of gravity, and 
the moments of inertia about the x-, y-, and z-axes: 

(a) the parallelepiped O^x^a, 0<^y?£b, Of^zSic; 

(6) the hemisphere Ogzg V(a 2 — a? — t/ 2 ); 

(c) the triangular prism with vertices (0, 0, 0), (a, 0, 0), (0, 6, 0), (0, 0, c). 



CHAPTER XI 

The Differential Equations 
for the Simplest Types of Vibration 

On several occasions we have already met with differential 
equations, that is, equations from which an unknown function 
is to be determined and which involve not only this function 
itself but also its derivatives. 

The simplest problem of this type is that of finding the inde- 
finite integral of a given function/(a;). This problem requires us to 
find a function y = F(x) which satisfies the differential equation 
y> —f(x) = 0. Further, we solved a problem of the same type in 
Chap. Ill, § 7 (p. 178), where we showed that an equation of the 
form y' = ay is satisfied by an exponential function y = ce°*. 
As we saw in Chap. V (p. 294), differential equations arise in 
connexion with the problems of mechanics, and indeed many 
branches of pure mathematics and most of applied mathematics 
depend on differential equations. In this chapter, without 
going into the general theory, we shall consider the differential 
equations of the simplest types of vibration. These are not only 
of theoretical value, but are also extremely important in applied 
mathematics. 

It will be convenient to bear the following general ideas and 
definitions in mind. By a solution of a differential equation we 
mean a function which, when substituted in the differential 
equation, satisfies the equation for all values of the inde- 
pendent variable that are being considered. Instead of solution 
the term integral is often used: in the first place because 
the problem is more or less a generalization of the ordinary 
problem of integration; and in the second place because 
it frequently happens that the solution is actually found by 
integration. 

601 



502 DIFFERENTIAL EQUATIONS [Chap. 

1. Vibration Problems of Mechanics and Physics 

1. The Simplest Mechanical Vibrations. 

The simplest type of mechanical vibration has already been 
considered in Chap. V, § 4 (p. 295). We there considered a 
particle of mass m which is free to move on the ataxia and which 
is brought back to its initial position x — by a restoring force. 
The magnitude of this restoring force we took to be proportional 
to the displacement x; in fact, we equated it to — he, where &is a 
positive constant and the negative sign expresses the fact that 
the force is always directed towards the origin. We shall now 
assume that there is a frictional force present also and that this 
frictional force is proportional to the velocity dx/dt = x of the 
particle and opposed to it. This force is then given by an expres- 
sion of the form — rx, with a positive frictional constant r. Finally, 
we shall assume that the particle is also acted on by an external 
force which is a function f(t) of the time t. Then by Newton's 
fundamental law the product of the mass m and the acceleration 
x must be equal to the total force, that is, the elastic force plus 
the frictional force plus the external force. This is expressed by 
the equation 

mx + rx + he = f(t). 

This equation determines the motion of the particle. If 

we recall the previous examples of differential equations, such 

dx 
as the integration problem x=-—=f(t) with its solution 

at 

x = J f(t) dt-{- c, or the solution of the particular differential 

equation mx + he — on p. 296, we observe that these problems 
have an infinite number of different solutions. Here too we 
shall find that there are an infinite number of solutions, which 
are expressed in the following way. It is possible to find a general 
solution or complete integral x(t) of the differential equation, 
depending not only on the independent variable t, but also on two 
parameters Cj and c 2 , called the constants of integration. If we 
assign special values to these constants, we obtain a particular 
solution, and every solution can be found by assigning special 
values to these constants. The complete integral is then the 
totality of all particular solutions. 



XI] THEORY OF VIBRATIONS 5°3 

This fact is quite understandable (of. also Chap. V, § 4, p. 298). We 
cannot expect that the differential equation alone will determine the 
motion completely. On the contrary, it is plausible that at a given instant, 
say at the time t = 0, we should be able to choose the initial position 
s(0) = x„ and the initial velocity £(0) =* * ( m short, the initial state) 
arbitrarily; in other words, at time t = we should be able to start the 
particle from any initial position with any velocity. This being done, 
we may expect the rest of the motion to be definitely determined. The 
two arbitrary constants (^ and c a in the general solution are just enough 
to enable us to select the particular solution which fits these initial con- 
ditions. In the next section (p. 508) we shall see that this can be done in 
one way only. 

If no external force is present, that is, if f(t) — 0, the motion 
is called a free motion. The differential equation is then said to 
be homogeneous. If f(t) is not equal to zero for all values of t, 
we say that the motion is forced and that the differential equa- 
tion is non-homogeneous. The term f(t) is also occasionally 
referred to as the perturbation term. 

2. Electrical Oscillations. 

A mechanical system of the simple type described can actually 
be realized only approximately. An approximation is offered 
by the pendulum, provided its oscillations are small. The oscil- 
lations of a magnetic needle, the oscillations 
of the centre of a telephone or microphone 
diaphragm, and other mechanical vibrations 
can be represented to within a certain degree ,uP 
of accuracy by systems such as we have ? 

described. But there is another type of *• £) ' 

phenomenon which corresponds far more <}>(*) 

exactly to our differential equation. This is 'fiectrica^clrcuft 7 
the oscillatory electrical circuit. 

We consider the circuit sketched in fig. 1, having inductance 
(i, resistance p and capacity C = 1/k. We also suppose that the 
circuit is acted upon by an external electromotive force <f>(t) 
which is known as a function of the time t, such as the voltage 
supplied by a dynamo or the voltage due to electric waves. In 
order to describe the process taking place in the circuit we denote 
the voltage across the condenser by E and the charge in the 
condenser by Q. These quantities are then connected by the 
equation CE = E\k = Q. The current I, which like the voltage 



n 



5o 4 DIFFERENTIAL EQUATIONS [Chap 

E is a function of the time, is defined as the rate of change of 
the charge per unit time, that is, as the rate at which the charge 
on the condenser diminishes: / = — Q ■= — dQ/dt = — EJk. 
Ohm's law states that the product of the current and the resis- 
tance is equal to the electromotive force (voltage); that is, it 
is equal to the condenser voltage E minus the counter electro- 
motive force due to self-induction plus the external electromotive 
force <f>(t). We thus arrive at the equation Ip = E — /*./ + <f>(t) 

ot—?-E=E + ?E+ 4>{t), that is, fiE + p E + kE= —Kd>(t), 

K K 

which is satisfied by the voltage in the circuit. We see, therefore, 
that we have obtained a differential equation of exactly the type 
considered in No. 1 (p. 502). Instead of the mass we have the 
inductance, instead of the frictional force the resistance, and 
instead of the elastic constant the reciprocal of the capacity, 
while the external electromotive force (apart from a constant 
factor) corresponds to the external force. If the electromotive 
force is zero, the differential equation is homogeneous. 

If we multiply both sides of the differential equation by 
— 1/k and differentiate with respect to the time, we obtain for 
the current / the corresponding equation 

id + /J + kI = 4(t), 

which differs from the equation for the voltage on the right- 
hand side only, and for free oscillations (<f> = 0) has identically 
the same form. 



2. Solution of the Homogeneous Equation. Free 
Oscillations 

1. The Formal Solution. 

We can easily obtain a solution of the homogeneous equation 
mx -+- rib + he = on p. 502 in the form of an exponential ex- 
pression, by seeking to determine a constant A in such a way that 
the expression e xt = x is a solution. If we substitute this and 
its derivatives x = Ae* 1 , x = A V in the differential equation 



XI] THE HOMOGENEOUS EQUATION 505 

and remove the common factor e*', we obtain the quadratic 
equation 

mA 2 4- rX + k = 

for A. The roots of this equation are 

Each of the two expressions x = e* 1 ' and x = e^'* is, at least 
formally, a particular solution of the differential equation, as we 
see by carrying out the calculations in the reverse direction. 
Three different cases can now occur. 

1. r 2 — Amk > 0. The two roots X t and Aj are then real, 
negative, and unequal, and we have two solutions of the differen- 
tial equation, x = v^ = e**' and x = u% == e x »*. With the help 
of these two solutions we can at once construct a solution in 
which two arbitrary constants are present. For on differentiation 
we see that 

x = c^ + c^ 

is also a solution of the differential equation. On p. 508 we shall 
show that this expression is in fact the most general solution of 
the equation; that is, that we can obtain every solution of the 
equation by substituting suitable numerical values for <\ and Cj. 

2. r 2 — imk = 0. The quadratic equation has a double root. 
Thus to begin with we have, apart from a constant factor, only 
the one solution x = w l = e~" t2m . But we easily verify that in 
this case the function 

x— w 2 — te~ nt2m 

is also a solution of the differential equation.* For we find that 

x=(l- — t) e~ rti2m , x = (— t - -\ e-"' 2 ", 
\ 2m I \4m 2 m) 

and by substitution we see that the differential equation 

r 2 
mx+ rx-\- — x=mx+rx-\-kx—0 
im 

* We are led to this solution naturally by the following limiting process: 
if X 1 4= A 2 , then the expression (e*i* — «*•«)/( A, — Aj) also represents a solution. 
If we now let \ t tend to A, and write A instead of A x , A„ our expression becomes 

* e \t „ U M 
aA 

IT (1798) 



«;o6 DIFFERENTIAL EQUATIONS [Chap. 

is satisfied. Then the expression 

x = c 1 e- rtlim + c 2 fe- r " 2m 

again gives us a solution of the differential equation with two 
arbitrary constants of integration c± and c 2 . 

3. r 2 — 4mk < 0. We put r 2 — 4mk = — 4m 2 v 2 and obtain 
two solutions of the differential equation in complex form, given 
by the expressions x— u^= e ~ rtl2m + irt and x= w 2 = e -r " 2 ' B-, ''". 
Euler's formula 

e ±,v ' = cos vt ii sin vt 

gives us for the real and imaginary parts of the complex solution 
«!, on the one hand the expressions 

v x = e ~ rtl!!m cos vt, v 2 = e ~ rt l 2m sin vt, 

and on the other hand the representation 

_ "i+m 2 _ _ %— M 2 
Vl 2~" ' " 2 2T" 

From the second form of representation we see that v t and v 2 
are (real) solutions of the differential equation. To verify this 
directly by differentiation and substitution forms a simple but 
valuable exercise. 

From our two particular solutions we can again form a general 
solution 

x = CjV x -J- <h% = ("l cos vt + c 2 sin vt) e ~ rtl2m 

with two arbitrary constants q and c 2 . This may also be written 
in the form 

x = ae~ rtl2m cos v(f — 8), 

where we have put c^ — a cosvS, c 2 = a siixvS, and a, S are two 
new constants. 

We recall that we have already come across this solution for 
the special case r = (Chap. V, § 4, p. 296). 

2. Physical Interpretation of the Solution. 

In the two cases r > 2-\/mk and r = 2\/mk the solution 
is given by the exponential curve, or by the graph of the function 
te~ nlZm , which for large values of t resembles the exponential 



XI] THE HOMOGENEOUS EQUATION 507 

curve, or by the superposition of such curves. In these cases 
the process is aperiodic; that is, as the time increases the " dis- 
tance " x approaches the value asymptotically, without oscil- 
lating about the value x = 0. The motion, therefore, is not 
oscillatory. The effect of friction or damping is so great that it 
prevents the elastic force from setting up oscillatory motions. 

It is quite different in the case r < 2^/mk, where the damping 
is so small that complex roots \, \ occur. The expression 
x= a cos v{t — 8)e~ rtl2m here gives us damped harmonic oscillations. 
These are oscillations which follow the sine law and have the 

circular frequency v ~ \ { 7~i)' ^ u * wnose amplitude, 

instead of being constant, is given by the expression ae~ rtlim . 
That is, the amplitude ciiminishes exponentially; the greater the 
expression r/2m is, the faster is 
the rate of decrease. In physical 
literature this damping factor is 
frequently called the logarithmic 
decrement of the damped oscilla- 
tion, the term indicating that the 

logarithm of the amplitude de- '[..^..((.^-^ 
creases at the rate r/2m. A Fie . 2 .-Dam P ed harmonic dilutions 
damped oscillation of this kind is 

illustrated in fig. 2. As before, we call the quantity T = 2n/v 
the period of the oscillation and the quantity v8 the phase 
displacement. For the special case r = we again obtain 
simple harmonic oscillations with the frequency v = Vk/m, 
the natural frequency of the undamped oscillatory system. 



3. Fulfilment of Given Initial Conditions. Uniqueness of the 
Solution. 

We have still to show that the solution with the two constants Cj and 
c 2 can be made to fit any pre-assigned initial state, and also that it repre- 
sents all the possible solutions of the equation. Suppose that we have to 
find a solution which at time t = satisfies the initial conditions x(Q) = x w 
sc(0) = *o> where the numbers x Q and aS can have any values. Then in 
case 1 on p. 605 we must put 

^1 "T c 2 — x o> 




508 DIFFERENTIAL EQUATIONS [Chap. 

Foi the constants Cj and c 2 we accordingly have two linear equations, and 
these have the unique solutions 

Aj Aj A2 Aj 

In case 2 (p. 505) the same process gives the two linear equations 

*, + *-*, (x— £) 

from which Cj and c 2 can again be uniquely determined. Finally, in case 3 
(p. 506) the equations determining the constants take the form 

a cos vS = x , 



with the solutions 



a( v sinvS cosvS ) = a! , 

\ 2m I 

\ ar ° oos ?- ° - \ V( vV + (*° + £ *»)'}• 



Thus we have shown that the general solution can be made to fit any 
arbitrary initial conditions. We have still to show that there is no other 
solution. For this we need only show that for a given initial state there 
can never be two different solutions. 

If two such solutions u(t) and »(t) existed, for which u(0) = x , 
ii(0) = x and t>(0) = x , v(0) = x w then their difference w = u — v would 
also be a solution of the differential equation, and we should have w(fi) = 0, 
j£(0) = 0. This solution would therefore correspond to an initial state of 
rest, that is, to a state in which at time t = the particle is in its position 
of rest and has zero velocity. We must show that it can never set itself in 
motion. To do this we multiply both sides of the differential equation 

mw 4- rw + lew = by 2u> and recall that 2wib = - to 2 and 2ww = — to*. 

dt dt 

We thus obtain 

t (mut) + i. (kw*) + 2nb* = 0. 
dt dt 

If we integrate between the instants t = and t = t and use the initial 
conditions w(0 ) = 0, w(0) = 0, we have 

r T /dw\" 
miv'iy) + kw*(t) + 2r {— J dt = 0. 

This equation, however, would yield a contradiction if at any time t > 
the function to were different from 0. For then the left-hand side of the 
equation would be positive, since we have taken m, h and r to be positive, 
while the right-hand side is zero. Hence to = u — v is always equal to 0, 
which proves that the solution is unique. 



XI] THE HOMOGENEOUS EQUATION 509 

Examples 

For the equations in Ex. 1-5 find the general solution, and also the 
solution for which «(0) = 0, x(0) = 1: 

1. * — Zx + 2x = 0. 

2. x + 3x + 2x = 0. 

3. 2x + x — x = 0. 

4. £ + 4x + 4x = 0. 
6. 4x + 4* + x = 0. 

6. Find the general solution, and also the solution for which x(0) = 0, 
sr(0) = 1, of the equation 

x + x + x = 0. 

Determine the frequency (v), the period (T), the amplitude (a), and the 
phase (S) of the solution. 

7. Find the solution of 

2x + 2x + x = 

for which a;(0) = 1, ac(0) = — 1. Calculate the amplitude (a), the phase (8), 
and the frequency (v) of the solution. 



3. The Non-homogeneous Equation. Forced Oscillations 

1. General Remarks. 

Before proceeding to the solution of the problem when 
an external force f(t) is present, that is, to the solution of the 
non-homogeneous equation, we make the following remark. 

If w and v are two solutions of the non-homogeneous equation, 
the difference u = w — v satisfies the homogeneous equation; 
this we see at once by substitution. Conversely, if u is a solution 
of the homogeneous equation and v a solution of the non- 
homogeneous equation, then w = u + v is also a solution of the 
non-homogeneous equation. Therefore from one solution * of 
the non-homogeneous equation we obtain all its solutions by 
adding the complete integral of the homogeneous equation, f 
We therefore need only find a single solution of the non-homo- 
geneous equation. Physically this means that if we have a forced 
oscillation due to an external force, and on it superpose an arbi- 
trary free oscillation, represented by a solution of the homo- 

• Often called the particular integral. 

t Often called the complementary function. 



510 DIFFERENTIAL EQUATIONS [Chap. 

geneous equation, we obtain a phenomenon which satisfies the 
same non-homogeneous equation as the original forced oscilla- 
tion. If a frictional force is present, the free motion in the case 
of oscillatory motion will fade out as time goes on, because of the 
damping factor e~ rtl2m . Hence for a given forced vibration with 
friction it is immaterial what free vibration we superpose; the 
motion will always tend to the same final state as time goes on. 
Secondly, we notice that the effect of a force /(«) can be split 
up in the same way as the force itself. By this we mean the 
following: if /$), f 2 (t), and f(t) are three functions such that 

and if x 1 = x^t) is a solution of the differential equation 
mx + rx + lex =f 1 (t) and x 2 = cc 2 (£) is a solution of the equation 
mx+rx+ kx=f 2 {t) then x(t) = x^t) + x 2 (t) is a solution of 
the differential equation mx + rx + kx = f(t). A correspond- 
ing statement of course holds if f(t) consists of any number of 
terms. This simple but important fact is called the " principle 
of superposition ". The proof follows from a glance at the 
equation itself. By subdividing the function f(t) into two or 
more terms we can thus split the differential equation into 
several equations, which in certain circumstances may be easier 
to manipulate. 

The most important case is that of a periodic external force 
f(t). Such a periodic external force can be resolved into 
purely periodic components by expansion in a Fourier series, 
and can therefore * be approximated to as closely as we please 
by a sum of a finite number of purely periodic functions. It is 
therefore sufficient to find the solution of the differential equation 
subject to the assumption that the right-hand side has the form 

o cos cot or b sin cot, 

where a, b, and at are arbitrary constants. 

Instead of working with these trigonometric functions, we can 
obtain the solution more simply and neatly if we use complex 
notation. We put f(t) = ce'"', and the principle of superposition 
shows that we need only consider the differential equation 

mx + rx -+- hx = ce*"*, 

* Provided that it is continuous and seotionally smooth (p. 439), which is 
the only case of importance in physios. 



XI] THE NON-HOMOGENEOUS EQUATION 511 

where by c we mean an arbitrary real or complex constant. Such 
a differential equation actually represents two real differential 
equations. For if we split the right-hand side into two terms, 
if e.g. we take = 1 and write e"" = cosarf + t ainwt, then 
%i and x 2 , the solutions of the two real differential equations 
mx + rx + fee = co&cot and mx + rx + kx = sinarf, combine to 
form the solution x = Xy + ix 2 of the complex differential equation. 
Conversely, if we first solve the differential equation in complex 
form, the real part of the solution gives ub the function a^ and 
the imaginary part the function x 2 . 

2. Solution of the Non-homogeneous Equation. 

We solve the equation mx + rx + Tex = ce' w by a device 
naturally suggested by intuition. We assume that c is real 
and (for the time being) that r 4= 0. We now make the guess 
that a motion will exist which has the same rhythm as the 
periodic external force, and we accordingly attempt to find 
a solution of the differential equation in the form 

x = ae ia \ 

where we have only to determine the factor a, which is indepen- 
dent of the time. If we substitute this expression and its deriva- 
tives x — taxxe*"", x = — to W*" in the differential equation and 
remove the common factor e"°' we obtain the equation 

— mafia -f- irwa + kcr = 



or 



— ma? -f irai -f- k 



Conversely, we see that for this value of a the expression ae* mi 
is actually a solution of the differential equation. To express 
the meaning of this result clearly, however, we must perform 
a few transformations. 

We begin by writing the complex factor a in the form 

k — ma? — ira> ... 

° *" c n »«■ 22 = cae ' 

(« — mut^Y + r 2 a> 2 

where the positive " distortion factor " a and the " phase dis- 



512 DIFFERENTIAL EQUATIONS [Chap. 

placement " to8 are expressed in terms of the given quantities 
m, r f h, by the equations 

a 2 = -., sinajS = rcoa, coswS = (k — mo) 2 )a. 

(k — mw 2 ) 2 + r 2 ca 2 

With this notation our solution takes the form 



and the meaning of the result is as follows: to the force c coswi 
there corresponds the " effect " ca cosa){t — 8), and to the force 
c smcot corresponds the effect ca sina>(£ — 8). 

Hence we see that the effect is a function of the same type 
as the force, that is, an undamped oscillation. This oscillation 
differs from the oscillation representing the force in that the 
amplitude is increased in the ratio a : 1 and the phase is altered 
by the angle cuS. Of course it is easy to obtain the same result 
without using the complex notation, but at the cost of somewhat 
longer calculations. 

According to the remark at the beginning of this section 
(p. 509), by finding this one solution we have completely solved 
the problem; for by superposing any free oscillation we can 
obtain the most general forced oscillation. 

Collecting the results, we have the following: 

The complete integral of the differential equation 

mx + rx + kx = ce*"' 

(where x =)= 0) is x = cae'™ (t_!) + u, where u is the complete 
integral of the homogeneous equation mx + r± + kx = and 
the quantities a and S are defined by the equations 

1 



(k — ma) 2 ) 2 + r 2 co 2 ' 



sincuS = rioa, coscoS = (k — mio 2 )a. 



The constants in this general solution leave us the pos- 
sibUity of making the solution suit an arbitrary initial state, 
that is, for arbitrarily assigned values of x and x the constants 
can be chosen in such a way that a;(0) = x and x(0) = x . 

3. The Resonance Curve. 

In order to acquire a grasp of the solution which we have 
obtained and of its significance in applications, we shall study 



XI] THE NON-HOMOGENEOUS EQUATION 513 

the distortion factor a as a function of the " exciting frequency " 
oj, that is, the function 

^ W ' = V(k — mw 2 ) 2 + rW* 

The reason for this detailed investigation is that for given con- 
stants k, m, r, or as we say for a given " oscillatory system ", 
we can think of the system as being acted on by periodic ex- 
citing forces of very different circular frequencies, and it is 
important to consider the solution of the differential equation for 
these widely different exciting forces. In order to describe the 
function conveniently we introduce the quantity a> = -y/k/m. 
This number a> is the circular frequency which the system would 
have for free oscillations if the friction r were zero; or, briefly, 
the natural frequency of the undamped system (cf. p. 507). The 
actual frequency of the free system, owing to the friction r, is 
not equal to co , but is instead 



V \m 4m 2 / 



where we assume that ikm — r 2 > 0. (If this is not the case the 
free system has no frequency; it is aperiodic.) 

The function <f>(a)) tends asymptotically to the value as the 
exciting frequency tends to infinity, and, in fact, it vanishes to 
the order 1/w 2 . Further, <f>(0) = 1/k; in other words, an exciting 
force of frequency zero and magnitude 1, that is, a constant 
force of magnitude 1, gives rise to a displacement of the oscil- 
latory system amounting to 1/k. In the region of positive values 
of a) the derivative <f>'(u>) cannot vanish except where the deri- 
vative of the expression (k — mco 2 ) 2 -f- rW vanishes, that is, 
for a value a> = oy l > for which the equation 

— 4mo)(k — mio 2 ) + 2r 2 cu = 

holds. In order that such a value may exist we must obviously 
have 2km — r 2 > 0; in this case 



y\m 2m 2 / V\ ° 2 2m 2 / * 



Since the function <f>(to) is positive everywhere, increases mono- 
tonically for small values of <a, and vanishes at infinity, this 



SH DIFFERENTIAL EQUATIONS [Chap. 

value must give a maximum. We call the circular frequency 
a»! the " resonance frequency " of the system. 

By substituting this expression for w x we find that the value 
of the maximum is 

V v» 4m 2 / 

As r -»• 0, this value increases beyond all bounds. For r — 0, 
that is, for an undamped oscillatory system, the function <f>(a>) 
has an infinite discontinuity at the value a> = w v This is a limit- 
ing case to which we shall give special consideration later. 

The graph of the function <f>(ao) is called the resonance curve 
of the system. The fact that for to = o> x (and consequently for 
small values of r in the neighbourhood of the natural frequency) 
the distortion of amplitude a = <f>(w) is particularly large is 
the mathematical expression of the " phenomenon of resonance ", 
which for fixed values of m and k is more and more evident as 
r becomes smaller and smaller. 

In fig. 3 we have sketched a family of resonance curves, all correspond- 
ing to the values m = 1 and k = 1, and consequently to to„ = 1, but with 
different values of D = $r. We see that for small values of D well-marked 
resonance occurs near co = 1; in the limiting case D = there would 
be an infinite discontinuity of <p(o>) at <o = 1, instead of a maximum. 
As D increases the maxima move towards the left, and for the value 
D = 1/V2 we have ^ — 0. In this last case the point where the tangent 
is horizontal has moved to the origin, and the maximum has disappeared. 
If D > 1/V2 there is no zero of <p'(to); the resonance ourve no longer has 
a maximum, and resonance no longer occurs. 

In general, the resonance phenomenon ceases as soon as the 
condition 

21cm — r 2 ^ 

becomes true. In the case of the equality sign, the resonance 
curve reaches its greatest height <£(0) = 1/k at to-^— 0; its 
tangent is horizontal there, and after an initial course which is 
almost horizontal it diminishes towards zero. 

1. Further Discussion of tbe Oscillation. 

We cannot, however, rest content with the above discussion. 
In order that we may really understand the phenomenon of forced 



XI] 



THE NON-HOMOGENEOUS EQUATION 



5*5 



motion an additional point requires to be emphasized. The 
particular integral cae"' ( ' -4) is to be regarded as a limiting state 
which the complete integral 

x(t) = cae , '"<'-*> +c 1 u 1 + c 2 u 2 

approaches more and more closely as time goes on, since the free 
oscillation c^ + c^u^ superposed on the particular integral 
fades away with the passage of time. This fading away will take 
place slowly if r is small, rapidly if r is large. 



]«_ 



2Z 

it 

fZ-0 
1-9 

is 

17 
1-6 
1-5 
H 

t '' 3 

X. ,., 

| 1-0 

C) 0-9 

0-8 

on 

0-6 
0-5 
04 
0-3 
0-2 
0-1 



OS 1-0 IS 20 

Exciting Frequency — *■ (»> 

Fig. 3.— Resonance curves 

Let us suppose, for example, that at the beginning of the 
motion, i.e. at time t = 0, the system is at rest, so that x(0) = 
and x(0) = 0. From this we can determine the constants q 
and c^ and we see at once that they are not both zero. Even when 
the exciting frequency is approximately or exactly equal to w l5 
so that resonance occurs, the relatively large amplitude a = ^(a^) 
will not at first appear. On the contrary, it will be masked by 
the function c^ + c^u^, and will first make its appearance when 
this function fades away; that is, it will appear more slowly 
the smaller r is. 





lr 


1 






D-Oj /D-lf 


\ \P-° 








\\ 






/ 


\\ 




J 


'/ 


\\ 




- ^^^ 


^D-i 


\\ 






^;& 


\\ 




\ X 


\i>-' \ 






- \ \ 


sP-2 






- \ 






^^ 


^■^ 


=8 ' 







516 DIFFERENTIAL EQUATIONS [Chap. 

For the undamped system, that is, for r = 0, our solution 
fails when the exciting frequency is equal to the natural circular 
frequency a> = Vk/m, for then ^(a> ) is infinite. We therefore 
cannot obtain a solution of the equation mx -f- kx = e*"' in the 
form ere""'. We can, however, at once obtain a solution of the 
equation in the form crfe""'. If we substitute this expression in 
the differential equation, remembering that 

x = ae , '"'(l -f- iwt), x = ae'"'(2iw — tat 2 ), 

we have 

oiflimco — mcoH -f- kt) = 1, 

and, since mu? = k, 



2imoi 



Thus when resonance occurs in an undamped system we have the 
solution 

t ,-..., t 



x = 



e* " = — -== e*" 



2ima) 2iVkm 

Using real notation, when/(<) = coswt we have x= - — sinwf, 

* Vkm 

and when/(<) = Binwt we have 

1 * 

x = — - cosarf. 

2 Vffwi 

We thus see that we have found a function which may be 
referred to as an oscillation, but whose amplitude increases pro- 
portionally with the time. The superposed free oscillation does not 
fade away, since it is undamped; but it retains its original ampli- 
tude and becomes unimportant in comparison with the increasing 
amplitude of the special forced oscillation. The fact that in this 
case the solution oscillates backwards and forwards between 
positive and negative bounds which continually increase as 
time goes on represents the real meaning of the i n fin it e discon- 
tinuity of the resonance function in the case of an undamped 
system. 



XI] THE NON-HOMOGENEOUS EQUATION 517 

5. Remarks on the Construction of Recording Instruments. 

In a great variety of applications in physios and engineering the dis- 
cussion in the previous sub-section is of the utmost importance. With many 
instruments, such as galvanometers, seismographs, oscillatory electrical 
circuits in radio receivers, and microphone diaphragms, the problem is to 
record an oscillatory displacement x due to an external periodic force. In 
such cases the quantity x satisfies our differential equation, at least to a 
first approximation. 

If T is the period of oscillation of the external periodio force, we can 
expand the force in a Fourier series of the form 

l_-«o 

or, better still, we can think of it as represented with sufficient accuracy by 

x 
a trigonometrio sum S y l efW"l' r ) t consisting of a finite number of terms 

1- -j 
only. By the principle of superposition (p. 510), the solution x(t) of the 
differential equation, apart from the superposed free oscillation, will be 
represented by an infinite series * of the form 

x(t)= £ a,^ 2 *' 2 ")', 

I— as 

or approximately by a finite expression of the form 

*(*)= S <,, e tf(2W2X 

I s 

In virtue of our previous results 

<7,= - r ,a,e-''¥2*'/D 

and 

1 27tZj. 2-Klr 

We can then describe the action of an arbitrary periodic external force 
in the following way: if we analyse the exciting force into purely periodio 
components, the individual terms of the Fourier series, then each com- 
ponent is subject to its own distortion of amplitude and phase displace- 
ment, and the separate effects are then superposed additively. If we are 
interested only in the distortion of amplitude (the phase displacement is 
only of secondary importance t in applications and, moreover, can be dis- 
cussed in the same way as the distortion of amplitude), a study of the 
resonance curve gives us complete information about the way in which 

* Questions of convergence will not be discussed here. 
\ Since e.g. it is imperceptible to the human ear. 



518 DIFFERENTIAL EQUATIONS [Chap. 

the motions of the recording apparatus reproduce the external exciting 

force. For very large values ofZorto(=-=n the effect of the exciting 

frequenoy on the displacement x will be hardly peroeptible. On the other 
hand, all exciting frequencies in the neighbourhood of <o„ the (circular) 
resonance frequenoy, will markedly affect the quantity x. 

In the construction of physical measuring and recording apparatus 
the constants m, r, and k are at our disposal, at least within wide limits. 
These should be chosen so that the shape of the resonance curve is as well 
adapted as possible to the special requirements of the measurement in 
question. Here two considerations predominate. In the first place, it is 
desirable that the apparatus should be as sensitive as possible; that is, for 
all frequencies to in question the value of a. should be as large as possible. 
For small values of <•>, as we have seen, a is approximately proportional to 
\jk, so that the number 1/k is a measure of the sensitiveness of the instru- 
ment for small exciting frequencies. The sensitiveness can therefore be 
increased by increasing l/k, that is, by weakening the restoring force. 

The other important point is the necessity for relative freedom from dis- 

tortion. Let us assume that the representation f{t) = £ f^^wirtt jg ^ 



i- 



adequate approximation to the exciting force. We then say that the 
apparatus records the exciting force f(t) with relative freedom from dis- 

tortion if for all circular frequencies <■> :& N — the distortion factor has 

approximately the same value. This condition is indispensable if we wish 
to derive conclusions about the exciting process directly from the behaviour 
of the apparatus; if, for example, a gramophone or wireless set is to repro- 
duce both high and low musical notes with an approximately correct ratio 
of intensity. The requirement that the reproduction should be relatively 
" distortionless " can never be satisfied exactly, since no portion of the 
resonance curve is exactly horizontal. We can, however, attempt to choose 
the constants m, k, r, of the apparatus in such a way that no marked 
resonance occurs, and also in such a way that the curve has a horizontal 
tangent at the beginning, so that tp(to) = a remains approximately con- 
stant for small values of a. As we have learned above, we can do this by 
putting 

2km — r 2 = 0. 

Given a constant m and a constant k, we can satisfy this requirement by 
adjusting the friction r properly, e.g. by inserting a properly chosen re- 
sistance in an electrical circuit. The resonance curve then shows us that 
from the frequency to circular frequencies near the natural circular 
frequency a> a of the undamped system the instrument is nearly 
distortionless, and that above this frequenoy the damping is considerable. 
We therefore obtain relative freedom from distortion in a given 
interval of frequencies by first choosing m so small and k so large that 
the natural circular frequency co of the undamped system is greater than 



XI] THE NON-HOMOGENEOUS EQUATION 519 

any of the exciting circular frequencies under consideration, and then 
choosing a damping factor r in accordance with the equation 
2km — r 2 = 0. 

Examples 

For the equations in Ex. 1-5 find the solution satisfying the initial 
conditions a;(0) = 0, sc(0) = 0. For equations 1-4 state also the amplitude, 
the phase, and the value of <o for which the amplitude is a maximum: 

1 . x + 3a6 + 2x = coaat. 

2. x + x + x = cos cot. 

3. x + x + * = sinfcrf. 

4. 2x + 2x + * = coscoi. 

5. x + 4x + ix = costoi. 



4. Additional Remarks on Differential Equations 

A more systematic study of differential equations is made 
in Volume II, Chapter VI. Here only a few additions to the 
preceding special theory will be given. 

1. Homogeneous Linear Differential Equations of Order n with 
Constant Coefficients. 

More complicated vibration problems lead to a linear differen- 
tial equation for the unknown function x(t) of the independent 
variable, of the form 

where c^, . . . ,a„ are constants and n is a positive integer. We 
can solve this by a method similar to that for the case n = 2 
(p. 504). 

Let x = c x '. If we substitute this function and its derivatives 
in the differential equation and remove the common factor e*', 
we obtain the following equation of the w-th degree for A: 

/(A) = A" + OiA"- 1 + • • • + o« = 0. 

If A is a root of this equation, e*' satisfies the differential equation. 
We shall now examine the various possibilities. Let A l7 Ag, . . . , 
A„ be the roots of the equation /(A) = 0, so that 

/(A) = (A-A 1 )(A-A 2 )...(A-AJ. 



520 DIFFERENTIAL EQUATIONS [Chap. 

First assume that all the roots are different. If all the A„'s 
are real, then we obtain n linearly independent solutions e*"', 
exactly as before. The general solution is any linear combination 

Cje* 1 ' -+- Cjje*'* + . . . + c n &* 

of these. The constants c„ can be so determined that x and its 
first n — 1 derivatives take arbitrary pre-assigned values at time 
t = 0. To do this we must solve the following system of n 
linear equations *: 

^ + 02+ ... + C„=x(0), 

A^ + A 2 e 2 + . . . + A„c„ = x'(0), 



K"- 1 * + A a "- 1 c 2 + . . . + A„«-ic„= ^-i»(0). 

If two of the roots are equal, say A x = Ag, then not only 
e x,f but also te Kt is a solution. This can be verified as follows: 
since /(A) = has a double root A = X 1 = )^, by a well- 
known theorem in algebra it follows that 

/'(A) = wA- 1 + (n - 1M- 2 + . . . + «„~i = 0. 
Now, by Leibnitz's rule for the derivative of a product (p. 202), 

* (to") = t-e" + k % ^ e w = <AV + hX*' 1 e". 
dt* dt k dtdt"- 1 

Substituting in the differential equation, we have 

te"(X»+a 1 X"- 1 + ...+ a„)+e x '(wA»- 1 +(w-l)a 1 A«- 2 + ...-\-a„_ 1 ) 
= te»f(X) + e Xt f'(X)=0, 

since /(A) = and by the above remark on double roots /'(A) = 0. 
In the same way if A^ Aj, . . . , A^ are equal, we obtain the 
following linearly independent solutions: 

e x '«, to*"', . . . r-V 1 ', 

which may be combined to give a general solution depending 
on Cj, Cg, . . . , c„. These parameters again enable us to adapt the 
solution to n pre-assigned conditions, so that for t = we can 
fix the value of x(0) and its first n — 1 derivatives. 

* This set of equations always has a solution if the roots are unequal, for 
the determinant of the coefficients is not zero. 



XI] HOMOGENEOUS EQUATIONS 521 

If the equation has complex roots, then by a theorem in algebra 
the roots occur in pairs, each one with its conjugate. Just as 
in the case n = 2, we obtain solutions of the form 

cos fit . e°* and sin/fc . e"', where \ = a + *yS, Ag = a — i/3. 
A few examples will serve to illustrate the above. 

Example 1. — + 2 — - - - 2x = 0, 

dfi dt* dt 

/(X) = X s + 2X a - X — 2 = 0. 

The general solution is x = c x e~* + c 2 e* + c 3 e~ ! '. 

A particular solution for which x = 2, *' = at t = is given by 
x = e' + e - '. 

d os tit or dx 

Example 2. — — — 4- x = 0. 

dt 3 <ft a <fc 

The general solution is x = c^e* + c^te* + c 3 e - '. 

^a»m^e 3. ??-2- + 4=0, 

/(X) = X» - 2X + 4 = (X + 2) (X - 1 + ♦) (X - 1 - »). 
The general solution is z — c^ - *' + c 2 e* cost + c 8 e* sint. 

2. Bernoulli's Equation. 

An equation of the type 

^+A(t)x=B(t), 

where A and B are functions of t alone, is called a linear equation. 
In the case B = 0, if x = a(t), x = ;8(i) are solutions, any linear 
combination of a and ft is also a solution. We shall now 
consider the slightly more general type 

^+A(t)x=B(t)x», 

where n is a positive integer. This is known as Bernoulli's 
equation. 

First consider the simpler case where B is zero, i.e. where 

^+A(t)x=Q. 
dt w 



523 DIFFERENTIAL EQUATIONS [Chap. 

dx 
Rewriting the equation as — = — A(t)dt, we see that it can be 

x 

integrated immediately as follows: 

logs = — jA(t)dt + c, 

if we write e° = v. 

Let us now try to satisfy Bernoulli's equation by a function of 
the form x = ve~i Adt , where we assume that v is a variable, 
so that 

dt dt 
Substituting, we have 

fo v — = Be—S A *et A *. 
dt 

which can be integrated at once, giving 

x i-« = (1 - w )e<»- 1 >P<" ffB&-*>S A "dt]. 

The above method is very important and may be applied 
in many cases. It is called the method of variation of para- 
meters. (For further details, see Volume II, p. 445.) Note 
that our solution is expressed in terms of integrals which can- 
not in general be expressed in terms of the elementary functions. 

Example. — Consider the equation 

— - tx = fix', 
dt 

Let x=*veS , *=ve i, ' ; 

then — — tx = — e" + vte v — tve u = — e ' , 

dt dt dt 

and the equation becomes 

dv u* 

dt v 

By integration, 

_ \ = (t* - 2)e*'' + c, or - = 2 - fi + ee'* 1 ". 
v * 

This result could have been obtained by direct substitution in the 
formula given above, but actually to carry the method through is far 
more instructive. 



<*V"=<W, or *L=fie v 'dt. 

.i2 



XI] SEPARATION OF THE VARIABLES 523 

3. Other Differential Equations of First Order Solvable by 
Simple Integration. 

There are a few other types of differential equations of the 
first order which can be solved by integration (although in most 
cases the integration cannot be performed explicitly in terms 
of elementary functions). 

The first method we shall consider is that of separation of the 
variables. If the differential equation can be brought into the 
form * 

A(x) dx + B(y)dy=0, 

the variables are said to be separable. The solution obviously is 

[A(x)dx+fB(y)dy + c = 0. 

Example. — Consider the equation 

yy" + xy* = x. 
Here 

ydy + x[y* — \)dx = 0, or y y + xdx = 0; 

hence 

ilog(y*-l) + ix i =e. or (j/ a - l)e*' = h. 

Another type of equation which can be solved is of the form 
M(x, y)dx+ N(x, y)dy = 0, 

where M and N are homogeneous functions of x and y of the 
same degree. In this case the fraction M/N is a function of y/x 
only, and we may write 

dy 
dx 



"©• 



If we put y =xv, this becomes 

X dx f 

The variables x, v are now separable as follows: 

dx dv 

x f(v) — v 

• That is, y'B(y) + A(x) = 0. 



524 DIFFERENTIAL EQUATIONS TChap. 

Integrating, we have 

logs = fjr^r — + c ' 

Example. — Consider the equation 

(2 Vxy — x)dy + ydx = 0. 

Substituting y = vx, we have 

(2c 1 " - l)x(v + x Y) + «» = °» 

v{2v xlt -l) + v+ x(2v*i* - 1) ~ = 0, 

ax 

*! = _ 2vl * ~ * <fo = — * + — 
~x 2« s ' 2 " » 2» s/2 ' 

Integrating, we have 

logo; = — log» — v~ * + e 
or 

logy 4- Vxjy = c. 

4. Differential Equations of the Second Order. 

There are a few types of non-linear differential equations 
whose solutions can also be found by integration. One type has 
already been discussed implicitly in Chap. V (p. 297) when we 
studied the motion of a particle on a given curve. This type 
is as follows: 

dP JK ' 

Let v = — , so that 
dt 

cPx __dv dv dx _ dv 

dfi ~~dl ~dxdl ~ dx' 



and our equation becomes 



dv ,. . 
v— =f{x). 
dx 



XI] SECOND ORDER EQUATIONS 525 

This may be regarded as an equation of the first order with v 
as dependent and x as independent variable. Separating the 
variables and integrating, we have 

vdv =f(x)dx 
« 2 = 2 J f(x) dx -\- or v = -y 2 jf{x)dx -f- e. 

Then 

dx 



^2jf(x)dx 



= dt, 



+ e 



which can be solved by integration (although in general it is 
impossible to carry out the integration explicitly). 

This device aids us to solve equations of the following types: 



,/riPx dx\ . 
.(d?x dx \ 
JdH dx \ 



which reduce respectively, when we write v = — , to 



*{'&'■*)=*■ 



These are equations of the first order which may be solvable 
by the preceding methods. This solution, after v has been re- 

placed by -, will again be a differential equation of the first 

order, which must be solved for x. A few examples will make 
the process clear. 



526 DIFFERENTIAL EQUATIONS [Chap. 

Example I. dy d*y . 

dxdx* 

Let -? = p. The equation becomes 
ox 

ox 
Integrating by separating the variables, we have 

op 2 = 3+0,, 

or 

Va^= Vx~+1^ 
ax 



By integration, 
Squaring, we have 
Example 2. 



Letf'= P . 
dx 



Va(y +c z )=* f (x + cj"*. 
a(y + e a ) s = f (x + c,) 8 



ax 8 ax 



xdx 







ix 


p 1 + #* 


Integrating, 


we 


have 








logp = — £ log(l + x 2 ) + e, 








P = Cl (i + x«r i/a , 


or 






dy °i 




dx Vl + x 2 ' 


whence 






y = c 2 + Cj ar sinhx. 


Example 3. 






" dx* \dxJ 


Let^ = 
dx 


= P. 


then<^ = 
dx 8 


- p ~. We have 






dp 
dy 


, „ pdp dy 
= 1 — p a , or J ^ = -s. 
1-p* Jf 



XI] SECOND ORDER EQUATIONS 527 

By integration, 

-4 log(I -p>) = logy + e, 



that is, 

or 

and 



y = Cl (l - p*r lft , 



2/ 2 (l - p*) = c,", 



f~ p - **-°*\ or **L- = dx. 

dx y Vyi — ^ 

Integrating, we have 

■VV - c, 2 - x + Cj, 
that is, 

y a = a? + C& + c 4 . 

Examples 
Solve the differential equations in Ex. 1-22. 

1. (1 + y*)dx - (j, - VT+^) (i + x f dy = . 

2. (x 3 + y*)dy = Zx*ydx. 3. y(loga; — logy)dy — xdx=0. 

4. »f/' + y = j/> loga;. 5. (1 + y*)dx = (arc tany — *)%. 

6. y^ + hy* = sina;. 

7. (aV + x*y* + xy + l)y + (afy 3 _ »V - **/ + 1)^ = . 

8. 3y V + y 3 =x—\. D. sina;eosy(te+oosa!sinj/iy=0. 

10. (1 + e xlv )dx + e* lv (l -*)dy = 0. 

«-S-»S+«S--i ».§+©■+«-* 

12.^-6^ + 9^=0. 18 ^ = ^ 

"■S-S+!=°- »<i--g+ »(|)=o. 

15. ^ — 2 rf,y ' - - " ■" <*** « ^^ 2 



+ 2,= 0. 21. s^?=2 (^Y 

<ft> w 



d* 8 <te*^ y * * «ft> *V<a 

M.«^=* 22.(1-^-^=2. 

da; 2 (ia; d« s dt 

23. Find the motion of a particle moving in a straight line under the 
attraction of a force varying as the inverse square of the distance from the 
origin. 



SUMMARY OF IMPORTANT THEOREMS 
AND FORMULAE 



1. Hyperbolic Functions. 

2. Convergence of Sequences and Series. 

3. Differentiation. 

4. Integration. 

6. Uniform Convergence and Interchange of Infinite Operations. 

6. Special Limits. 

7. Special Definite Integrals. 

8. Mean Value Theorems. 

9. Expansions in Series: Taylor Series, Fourier Series. 

10. Maxima and Minima. 

11. Curves. 

12. Length of Arc, Area, Volume. 



1. Hyperbolic Functions 

(pp. 183-189) 

^ , sinha; e* — e~°° 

sinha; = ««- - «-). tanhs = _ = ^-~. 

cosh* = *(e" + e"«). cotha; = ^ = j±£ 

ooah>« - sm&x = 1. cosh** = _ i-^. 

cosh (a; + y) = cosha; coshy + sinha: amhy. 

emh(x ±y) = sinha; coshy ± cosha; sinhy. 

eosh 2 a; = £(cosh2a; + 1). sinh 2 x = |(cosh2a; — 1). 

ar sinha; = log{x + s/(x* + 1)}. 

ar cosha; = logla; + y/{pP — 1)} (x ;> 1). 

18 629 (E7981 



53© SUMMARY OF FORMULA 

1 4- x 
ar tanha; = \ log —I— (| x I < 1). 
1 — x 

X -+- 1 

ar cothz = £ log (| x I > 1). 

a; — 1 



2. Convergence of Sequences and Series 

1. Infinite Sequences (p. 38). 

Gauchy's Convergence Test (p. 40). A sequence of numbers 
a n is convergent if, and only if, for every positive quantity c 
there exists a number N such that 

I a» — ««. | < e 

when n > N, m> N. 

Operations with limits (pp. 41-42). If lima n and lim&„ exist 
then «->» ii-*- » 

lim(a„ + b n ) = lima„ + lim&„; 

« — >-ao b— >-oo n— >-oo 

lim(a„.6„)= lima„ . lim&„; 

#i— >-ao n— >ao 71— >-oo 

limo„ 

lim ^" = "~ >0 ° , provided lim&„ 4= 0. 
n->ooO n Iimo„ i»-*-« 

«->-00 

2. Infinite Series (p. 365 et seq.). 

Gauchy's Convergence Test (p. 367). The series Sa n converges 
if, and only if, for every positive quantity e there exists a number 
N such that 

I On + « +l + • • • + Offl I < « 

when m > n > N. 

Note. — All the following criteria are sufficient but not necessary. 

Principle of comparison of series (p. 377). Ea„ converges 
if numbers b n exist such that b n 2g | o„ | for all values of n and 
Eft„ converges. 



CONVERGENCE 



53* 



Ratio test and root test (p. 378). So„ converges if there is a 
number N, and also a number q < 1, such that 



a n+\ 



<q or y I a n | < q 



for all values of n > N; in particular, if there is a number k < 1 
such that 



lim 



*n+l 



= k or lim -y/ 1 o„ | = A. 



Sa„ diverges if there is a number k > 1 such that 



lim 



°n+l 



= k or lim -(/ 1 a n \ = k. 



Leibnitz's Test (p. 370). Sa n converges if the terms have 
alternating signs and | a n | tends monotonically to zero. 



3. Differentiation 

1. General Rules (Fundamental Ideas, p. 88 et seq.), 

{/(*) ± £(*)}'=/'(*) ± •(*)• 
{/(*)*(*)}' = f\x)g{x) + f(x)g'(x). 

W)/ (<K*)} 2 



> 9¥i 4= (pp. 136-139). 



{f(x)g(x)}M = /W {x) g( x) + Qf-^\x)g'(x) 

+ (l)f n - 2) (*)9"(*) + • • • +f(x)g^(x). 
(Leibnitz's Rule, p. 202.) 



Chain rule. If f(x) = g{<f>(x)}, 

df dg d(f> 

dx d<f> dx 



dx* 



d*g /MY , dg d 2 <b , 
= JTl ( -T I + lh. X5' and so on (PP- 



532 SUMMARY OF FORMULAE 

If u = /(£, t), i, . . .), where £ = £{x, y), i? = r)(x, y), . . . , 

«.=/«£. +f v V x +f(Zm + • • • » 

«_ =/«£•■ +/™ 1 ?* 2 +/?<r£* 2 + . . . 

+ 2/ h *.ij. + 2/« £,£„+... 
+ 

+ f(£x* + fr,Vxx +fitxx + • • • , 

with corresponding formulae for u xy and w„„ (p. 476). 
Implicit functions. If F(x, y) = 0, 

dx F v 

®y_ = __ F xx F y *-2F xv F x F v +F vv F x * 

dx 2 F* ^' 



Functions expressed in terras of a parameter. If x = x{t), 

V = »(«). 

dy = dyldx (p 262) 

dx dt/ dt 

Inverse functions. 

^=l/^ (p. 145). 

dx I dy 

If £ = #&, y), 7) = 0(a;, y), 

dx_t/j v dx___^y dy = __ l h <ty_—$? 
H~D'd : n D' d£ D' d n D' 

where 

<f>x <t>v 

(functional determinant or Jacobian) (p. 479). 



d{x,y) 



ff> x >py — <f>y^x 



2. Special Formulas (pp. 94-96, 139-141, 149-150, 167 et seq., 
186-187). 

(a;")' = nx n ~K 

(sin a;)' = cos a;. (arc sin a;)' = 



(cosx)' = — sina;. (arc cosa;)' = 



1 



V(l - a?) 



DIFFERENTIATION 533 

(tana;)' = — — = sec 2 2;. (arc tana;)' = 



cos 2 x 1 + x 2 

(cota;)' = — =-s- = — cosec 2 a;. (arc cotx)' = 



sin 2 a; l + i 2 

1 



(sinha;)' = cosh a;. (arsinha;)' = 



(cosh a;)' = sinhx. (ar cosh a;)' = + 



1 



(x > 1). 

(tanha;)'= _— — = sech 2 aj. ( ar tanha;)' = 1 . ( I x I < 1). 
cosh z a; ' \ — ar 

(cotha;)'= — _^=-cosech 2 a;. (ax cotha;)' = — — ( I x I > 1). 
sinh 2 a; x ' 1 — x 2 

(log a x)' = - log„e; ( a *)' = a * l g, a; 

in particular, in particular, 

ogx)' = -. 

x 

(«")' = U V (VU'/U + »'logM), 



(logx)' = -. (e')' = e?. 

X 



4. Integration 
1. General Rules (Fundamental Ideas, p. 79 et seq.). 
ff{x) dx + fj(x) dx =f f(x) dx. 

f a f(x) dx = — f b f(x) dx. 
f a {/(*) + 9(x)}dx =f a f(x) dx +f a g(x) dx. 

J cf{x) dx— c I f(x) dx (pp. 81 et seq., 141). 

Estimation of integrals. If /(#) 2; g{x), b^a, 

r b r b 

I f(x) dx ^ / g(x) dx (p. 126). 

J a J a 



534 SUMMARY OF FORMULA 

Integration by Parts (pp. 218-219). 

J a f(x)g'(x) dx = f(x)g(x) ||-jf * f'(x)g(x) dx. 

Method of substitution (pp. 207-212). 

fj(x) dx =f" f{<t>(u)}<f>'(u) du, 

where a = <j>(a), b = c£(£). 

Connexion between differentiation and integration (p. Ill et seq.). 

Improper Integrals (pp. 197-254). 

If f(x) is continuous except at the point x = b where it 
becomes infinite, / f(x) dx is (absolutely) convergent, if in the 
neighbourhood of x = b 

UK n ~ (b-x)"' 
where v < 1 (p. 248). 

J f(x)dx converges (absolutely) if 

i/<*>is£ 

where v > 1, for values of x 2> A (p. 250). 

2. Special Formulas (pp. 82-87, 128-130, 142 et seq., 151, 168 
et seq., 206, 208-209, 210, 213-217, 220 et seq.). 

J x n dx= . Jhgxdx= xlogx— x. 

- = log I x |. J - logs & = J (log x) a . 

sMoga;<Za;=— — (logx — ); o=)=-l. 

a + 1 \ a + 1/ 



INTEGRATION 535 

f sinx dx = — coax. /sinhx dx = coshx. 

J coax dx = sinx. /coshx dx = sinhx. 

/ tana; dx = — log | cosx |. /tanhx dx = log coshx. 
fcotxdx = log I sinx |. fcothx dx = log| sinhx |. 

Tare shixdx = x arc sinx + -\/(l — x 2 ). 
/ arc cosx<Zx = x arc cosx — -\/(l — x 2 ). 
/ arc tanxefee = x arc tanx — \ log(l + x 2 ). 
Tare cotxefce = x arc cotx -f- \ log (1 + x 2 ). 

Tar sinhxrfx = x ar sinhx — -\/(l + £*)• 
Tar coshxrfx = x ar coshx — \/(x 2 — 1). 
/ar tanhxefc = x ar tanhx + £ log(l — x 2 ). 
Tar cothxtfx = x ar cothx -+- \ logfx 2 — 1). 

/dx 1 L x I r dx , I , , x I 
= log tan- . / -— — = log tanh - . 
sinx I 2 1 J sinhx | 2 1 

/ = log tan 1 - + - 1 / — r— = 2 arctan I tanh J 

J cosx 6 | \2 4/1 J coshx \ 2/ 

= 2 ar tanh ( tan - I. 

/- = log I tanx I. /-— — = log I tanhx I. 

J sinx cosx J sinhx coshx 

/dx r dx 

-— - = —COtX. / . , = —COthX. 

sin a x J sinh^x 

/dx c dx , 

— — = tanx. / — — - = tanhx. 

cos z x J cosh 2 x 



536 SUMMARY OF FORMULAE 

Jsm 2 xdx = \(x — sina; cosz). 
I cos 2 xdx = $(x -+■ sina; cosa;). 



dx 



— arc tan ( - tana; J 
ao \b / 

/ . . , ri r = ~ -j-artanhf^tana;) 

J a'Bm^x— b 2 cos 2 x ao \b /) 



J a 2 sin 2 a; -f- b 2 cos 2 a: 
dx 



a, b 4= 0. 



/•da; I ^ x 

/ 3-r— , = arc tan -. 
J x 2 + a 2 a a 



ar tanh = — log ?, if I x I < a. 

/dx \ a a 2a a-\-x 

*"-»* | 1 x 1 x—a 

- ar coth - = --- log , if I x I > a, a > 0. 

a a 2a x+a 



/dx 
Via 2 - x 2 ) ' 



4- arc sin' 



dx 



-arc cos . 
a 



a f dx 

x J xVix 2 — a 2 ) 



1 . a 

— arc sin - . 
a x 

, 1 a 

+ arc cos-. 

a x 



f 



xdx 



= V(« 2 + x 2 ). 



Via 2 + x 2 ) 

/xdx . 

dx 
V> 2 "+ * 2 ) 

dx 
V& 1 - a 2 ) 

dx 



f V (a 2 +x 2 } = ar Shih a = l0g ^ ±a: + V{X * + fl2) >- 
--3-— - ar cosh . = log{x ± V(* a ~ a 2 )}. 



xVix 2 -\-a 2 ) 
dx 



1 
a 



f „f, „, = - I ars inh a =- 1 ln g ±^±V(g 2 + ^) 



log 



1 , a 1 . a + Via 2 — x 2 ) 

// 2 2^ = ~' ai cosh = — lo g -=-?- — . 

Via 2 — x 2 ) a x a x 



r ax 
J xVia 2 — : 



INTEGRATION 



537 



/ \/{a 2 — x 2 )dx = — a 2 arc cos - + - x^/(a 2 — x 2 ). 

f-\/(x 2 — a 2 ) dx = — - a 2 ar cosh + - x y/(x 2 — a 2 ). 

IVi® 2 + a 2 )dx= - a 2 ar sinh - -f- - x ^/(x 2 + a 2 ). 
J 2 a 2 

f: 



dx 



x 2 +2bx+c \/{b 2 — c) 

1 



2^{b 2 -c) 



aitanh 



log 



x+b 
V(b*-c ) 
V(b 2 -c) — x—b 
V(6 2 - c) + x+b 



if c < b % , i.e. x 2 -f- 2bx -\- c = has real roots. 



/ 



dx 



arc tan 



sc+6 



x 2 + 26x + c V(« - &2 ) " " V(« - &2 )' 

if c> 6 2 , i.e. (E 2 + 26x -f c = has imaginary roots. 



e ax sinbxdx = e ox (a sin bx — b cos&r). 

a 2 + b 2 v 

/I 
e oa! cos fee dec = e ax (a cos foe + b sin fee). 
a 2 + o 2 



/sin"a;cosa;aa; = 

J n+1 

Recurrence Formulce (p. 221 e£ seg.). 

cos n xdx = - cos n_1 a; sina; -\ / cos n-2 a;<fcc. 

n n •> 

fsm n xdx — — - sin n_1 a; cos a; + / sin n_2 a;tfa;, 

J n n J 

fx n cosxdx = x n since — n Jx"' 1 sinxdx. 

fx n smxdx = — x n cosx + n \x n ~ x cosxrife. 

/• , sin m+1 a;cos n-1 a; , n — 1 

/si 



sin™ x cos" x dx = 



m + n 



■ + 



m + 



-7' 



sin m xcos n-2 a;ia;. 



18* 



( IS 798) 



538 SUMMARY OF FORMULA 

j(logx) n dx = a;(logx) n — n uloga;)" -1 ^. 

fx n e x dx = x"e x — n fx"~ 1 e x dx. 

^(log^fc^ ^'y - -4- [x°(hgx)»-idx (a =f* -1). 

f dx _ x In — S r dx 

J (1 + z 2 )" "" 2(n-l)(l + ai»)"- 1 2(n— lj^l + aj 8 )"- 1 ' 

3. Integration of Special Types of Functions. 

(a) Rational Functions. These are reduced to the following 
three fundamental types by resolution into partial fractions 
(pp. 226-234): 

r dx 1 1 

J (x — a) n ~~ n — 1 (a; — a)" -1 ' 

r dx 1 r du 

J (x* 4- 26a; 4- c) n ~ (c — 6 2 ^-* J '( 



(a? 4- 2bx 4- c) n (c — 6 2 )"-* •/ (1 4- ««)»' 
where c — 6 2 > 0, w = (a: + b)/\/(c — 6 2 ), 

the integral on the right being evaluated by the last recurrence 
formula given above; 



/ 



xdx 



(x 2 4- 2bx 4- c) n 

1 1 , r dx 

x 4- c)" -1 J ( 



2 (n — 1) (x* 4- 26a; + c)"" 1 ./ (cc 2 + 26a;4- c)"' 



where the integral on the right is of the type immediately pre- 
ceding. 

In what follows R denotes a rational function. 
(6) jR(sinx, cosx)dx (p. 237). 

Substitution: t =•= tan , so that sin a; = , cos a; = 

dx_ 2 2 l + i2 1 + * 2 ' 

A 1 + t*' 



INTEGRATION 539 

If, however, R is an even function or involves tana; alone, the 
following substitution is more convenient: 

i -a « 2 e 1 dx 1 

u = tana;, sin 2 x = — — , cos 2 x = — — , — = — — -. 
1 + u 2 1 + u 2 du 1 + u 2 



x 2t 1 + < 2 

Substitution: «= tanh -, so that sinh x= cosha;= -J— > 



(c) JR(coshx, sinha;)<& (p. 237) 

Substitution: «= tanh-, so that s„~~ 

dx_ 2 2 1 ~ t > 1_ 

<ft 1 - P 

(d) fR(^">)dx. 

Substitution: t = e""", — = — . 
at mt 

(e) fR{x, V(l - a: 2 )) da: (pp. 237-238). 
Substitution: 

(/) yi2(«, V(x* -l))dx (p. 238). 
Substitution: 

1 V W+i/' ~ r^ 2 ' V( "r^T 2 ' s ~ a - < 2 ) 2- 

(g) y*i?(x,V(l + ^ 2 ))<fe(p.238). 

Substitution: 

i // » i i\ <2 ~ 1 // i i i\ 1 + fi dx t2 -fl 

t = x + \/(z* + 1), X = — - — , \/(x 2 + 1) = — ■ — , — = — l —. 
^ v v ~r ;> 2* Y v ' 2t (ft 2f 2 



(1+* 2 ) 2 



(A) /fifo Vfa** + 26a; + c))(& (p. 239). 

. j, aaM 

The substitution f = — n 

Vl «w- 
one of the three preceding types, 



_ CLX I ■ 6 

The substitution £ = — n — , reduces this integral to 

Vl ac— 6 2 | 



S4o SUMMARY OF FORMULA 

(t) [R(x, y/(ax + b), V(«b + d))dx (p. 239). 
Substitution: £ = ^/{cx + d) or x = - (£* — d), — = — 



(i) /<^(^))^ (p - 240) - 

Substitution: 

f V \« + «*/' c£» - a' d£ (c£» - a) 2 



5. Uniform Convergence and Interchange of Infinite 
Operations 

For the definition of uniform convergence see p. 391. 

A series which is uniformly convergent in a closed interval 
and whose terms are continuous functions represents a con- 
tinuous function in that interval (p. 393). 

If \fjx) | ^ a„ and Sa„ converges, S/„(a;) converges uniformly 
(and absolutely) (p. 392). 

Interchange of Summation and Differentiation pp. 396-397). Any 
convergent series of continuous functions may be differentiated 
term by term, provided the resulting series converges uniformly. 

Interchange of Summation and Integration (p. 394). Any 
uniformly convergent series of continuous functions may be 
integrated term by term. The resulting series also converges 
uniformly. 

6. Special Limits 

Stirling's Formula (p. 361). 

n! 



lim 



,V2^n n+i e-» 

Wallis's Product (pp. 223-225, 363, 445). 

1= n ( 2w 2n \ 

2 — „_! \2n - 1 In + 1/ 

,. (n!) 2 2 2n 
Vir = lim -5 — - — — . 
v „-+ao{2n)\^n 

(For infinite products, see pp. 419-422). 



SPECIAL LIMITS 541 

«" = Km (l + -Y (p. 175). 

i (s) = s - = n _L_ « > 1 ( P . 420). 

„=ltt* p 1 — p * 

00 / x 2 \ 
sinwc = 77a; II ( 1 1 (p. 445). 

Definition of the Gamma Function (pp. 250-251). 

T(x) = fe-H'^dx (x ^ 1): 
■'0 

r(* + i; = xr(x); 

if x is a positive integer n, 

T(n) = (n - 1)! 

Order of magnitude of functions (pp. 190-195). 

lim — = 00, if c > (p. 192). 

ft— >oo X" 

lim !££? = 0, if a > (p. 192). 

*-»ao X* 

lim x* logx = 0, if a > (p. 195). 

«->o 

7. Special Definite Integrals 
Orthogonality relations of the trigonometric functions (p. 217). 

f + " . . , (0, if m 4= n. 

I sinmx sinnxax — { ., , „ 

J-* Itt, 11 m = n, n =)= 0. 

/ sinmx cosnx da> = 0. 

r + * , (0, ifm=f=n. 

/ cosmx cosnx ax ={ ., , „ 

^-■r In-, 11 m = w, n 4= 0. 

jTV-'dx^V (P- 496). 

£ !™£ (fo = I „ (pp. 251-253, 418, 450). 



542 SUMMARY OF FORMULA 

8. Mean Value Theorems 
Mean Value Theorem of the Differential Calculus (p. 103). 

f{x + h) - f{x) =f(x+eh), o<0<i. 

A 

If f(x)—f(x+ h) = 0, this gives Rolle's Theorem (p. 105): 
between two zeros of the function there is always a zero of 
the derivative. 

Generalized Mean Value Theorem (pp. 135, 203). 

f(b)-m _nt) 

9(b) -g(a) g'(i)' 
where f is a value between a and b. 

Taylor's Theorem (pp. 320-323). 

f(* + A) =/(*) + £ /'(*) + ~f"(x) + . . . + £/*•»(*) + Rm 

with the remainder (pp. 323-324). 

K = ^ / * (h - T)»/ ( " +1) (* + T)dT 
h"* 1 



(n + 1)! 



/««+«(» +0A) 



«."(!_ 0)» /(«+« (35 + A ) (0 < < 1). 

Afean Value Theorem of the Integral Calculus (p. 127). 
f*f(x)dx = (6 — a) f(£), where a ^ f ^ 6. 
ff(x)p(x) dx =/(£) ^(z) <fcc, if p(x) ^ 0. 



EXPANSIONS IN SERIES 



543 



9. Expansions in Series: Taylor Series, Fourier Series 

1. Power Series (for definition, see p. 398). 
(a) Power Series in General. 



Any power series 



R-0 



in one variable has a radius of convergence p (which may be zero 
or infinite); the series converges when | x\ < p, and in fact it con- 
verges uniformly and absolutely in every interval | x | ^ 17, where 
7) < p; when | x | > p, the series diverges (p. 400). 

If the remainder in Taylor's theorem tends to zero as n 
increases, we have the infinite power series (p. 325) 

fix + h) =/(*) + */' (x) + *f"(x) +... + ^f\x) +.... 

(b) Special Taylor Series (pp. 316-319, 326-330, 405-409, 
422-423). 

iog(i + *) = *-£ + J- 5 + -... + (-ir l - + .-- 

for — 1< x ^ 1. 

) 






x in+l 



sinx=x-^ + |;- + . ..+ (-!)« (2n+i)! 
00.. -.1--, + -- + . .. + (-!)» — + . 



+ 



for all 
' values 

Of 3. 



X 8 3* , X 2b+1 

sinhx = 2; + — + — +...+ 

S! 51 (2n + 1)! 



+ 



cosha; = 1 + + - + 



(2n)! 



+ 



„_i (2v)! 



for--<»<-, 



2/COtZ 1 



2 2 "B„ 



S (_i)-H_^?'iB 8 ' for— 7T<x<it, 
v-o (2v)! 



where the quantities B 2t , are Bernoulli's numbers (p. 423). 



544 



SUMMARY OF FORMULA 



. la* , 1.3a* , 1.3.5a; 7 , 

arc sinx = x + — + -A — + . . . 

2 3 2.4 5 2.4.6 7 

. , la? , 1.3a? 1.3.5 x 1 , for 

ar sinha; = x — \- ... V z. - , 

2 3 2.4 5 2.4.6 7 -l^^l- 

x 3 x 5 
arc tanas =x— — + — 1-... 

artanhx = as + — -f — + ... for|x|<l. 



Binomial Series. 

(1 + xf 

, , , o(a — 1) , . 



in particular, 
1 



a(a-l)(g-2)...(a-n+l) 

d -* + -'- 

for — 1 < x < 1, 

if a > — 1 for x = 1 also, 
if a S: for a; = — 1 also; 



= 1 — x-\- a? — a? -\ ... 

= 1 — 2x + 3a; 2 — 4a? + — 



1 + as 

1 

(1 + xf 

1 , 1 , 1.3 . 1.3.5 , , 1.3.5.7 . , 

=1 — -xA x a a? A or r ••• • 

V(l + x) 2 ^2.4 2.4.6 ^2.4.6.8 



X 



Elliptic integral: 



V(l- ^sinV) 



{^©"^GrO'^Gifr^-}' 



EXPANSIONS IN SERIES 545 



2. Fourier Series. 

If the function f(x) is sectionally smooth in the interval 
—17 ^ x ^ 77, i.e. if its first derivative is sectionally continuous, 
the Fourier series 

1 °° 

f(x) = - a + S (a, cos vx + o„ sin vx), 



2 



1—1 



where 0,= - f /(<)cosvi<&, 6,= - f /(*)sinv<<ft 

TlJ—rr TI J —Tt 

is absolutely convergent throughout the whole interval. If 
f{x) has a finite number of jump discontinuities, while elsewhere 
f'(x) is sectionally continuous, the series converges uniformly in 
every closed sub-interval which contains no discontinuities of 
f(x). At every point at which f(x) is continuous, the series 
represents the value of the function f(x), while at every point 
of discontinuity of f(x) it represents the arithmetic mean of the 
right-hand and left-hand limits of f(x) (pp. 447-450). 



10. Maxima and Minima 

The following rule holds only for maxima and minima in the 
interim of the region under consideration. 

In order that £ may be an extreme value of the function 
y = f(x), f'(g) must vanish. When this condition is satisfied there 
is a maximum or minimum if the first non- vanishing derivative 
of f(x) is of even order; if it is of odd order, there is neither a 
maximum nor a rninimum. In the former case there is a maximum 
01 a minimum according as the sign of the first non-zero deri- 
vative is negative or positive (p. 158 et seq.). 



11. Curves 

In what follows £, -q are current co-ordinates. 
Equation of the curve: 

(«) y =/(*), (&) -Ffo y) = °> («) * = * W, y = * W- 



546 SUMMARY OF FORMULA 

Equation of the tangent at the point (x, y) (p. 263): 
(o) , - y = (£ - x)J'{x), (b) ($- x) F„+{ri- y) F v = 0, 
(«){*-* (') }f (0 - {v - (0 } M) = 0. 

Equation of the normal at the point (x, y) (p. 263): 

(o) f - * + (ij - ?)/'(*) = o. (&) (*- *)*.- to - y)*. = 0, 
(c) {£- <£(*)}f M + {*? - *(0}f (0 = o- 

Curvature (p. 281): 

. . 7 y" /M t F xx F v i —2F xv F x F y + F^FJ 

{a) h ~ ("!+?¥' (6) . ... W+W ' 

Radius of curvature (p. 282): 

1 



Evolute (locus of centre of curvature) (pp. 283, 307-311): 
1 4- w' 2 .1 + V' 2 

{a)i=X -y>L±JL, v =y+^; 

P 2_|_ p 2 

(6) £=*+*. ^^ a _ 2F xv fJ v + F„F„» ' 

Involute (p. 309): 

| = a; + (a— s)*, tj = y + (a — *)& 

where a is an arbitrary constant and s the length of arc measured 
from a given point. 

Point of inflection (pp. 159, 266). Necessary condition for a 
point of inflection is 

(a) y"= 0, (6) F„F* - 2F XV F X F V + F„F* = 0, 
(c) xy—xy = 0. 



CURVES 
Angle between two curves (p. 264): 



547 



(b) cosa> = 



VW+^VOvW+W 



(c)cosa, **i + m 

V(* 2 + y 2 )V(V + 2/! 2 ) 

In particular, the curves are orthogonal if 

(6) F X G X + F V G V = 0, (c) x*! + yy t = 0; 

the curves touch if 

(6) F X G V - F V G X = 0, (c) s& - ^y = 0. 

Two curves y=f(x), y = g{x) have contact of order n at 
a point x, if 

/(*) = *(*), /'{*) = ?{*), .... /^^"V), 

/ (n+1) (a')*5r ( ' ,+1) ^) 
(pp. 331-333). 

12. Length op Abc, Akea, Volume 

Length of Arc (pp. 276-280). Let a plane curve be given by 
the equations 

(a) y =f(x), (b) F(x, y) = 0, (c) z = <f> («), y = 0(0. 
(<Z) (polar co-ordinates) r = r(0). 

The length of arc is 
(a) • = /V(l + V' 2 )dx, (c) « = /"V(* 2 + 2/ 2 )*> 

® * = PI vW + F*)ix, (d) s = f 1 V(r 2 + r' 2 ) «W. 

Area of Plane Surface. The area bounded by the curve 
r=r(0) 

and two radii vectores 6 , 6 V where r, are polar co-ordinates, 
is given by 



lpr*d6 (p. 275). 



548 SUMMARY OF FORMULA 

The area enclosed by the curve 

y=f(x), 

the two ordinates x = x , x= x 1 , and the x-axis, is 

Cy&x (p. 80). 

Volume. The volume lying over the region R and bounded 
above by the surface with the equation 

2 =f(x,y) 
is given by 

V=fff(x,y)dxdy (p. 487). 



MISCELLANEOUS EXAMPLES 



CHAPTER I 



1. Prove that if p and q are integers the expansion of p/q as a decimal 
either terminates or recurs from a certain point onward. Prove also that 
every terminating or recurring decimal represents a rational number. 

2. Express 39 in the ternary scale (scale of 3). 

3. How would the number one hundred and fifty-six be written if (a) 
the binary scale (scale of 2), (6) the scale of 4, were in common use? 

4. Express the following numbers in the scale of 12: (a) 1076, (6) 10,000, 
(c) 20,736, (d) 1/6, (e) 1/64, (/) 1/5. 

5. We can find V 2 to one decimal place thus: I s = 1 < 2, 2 2 = 4 > 2, 
therefore 1< V2 < 2. Next, l-3 a = 1-69 < 2, l-4 a = 1-96 < 2, l-5 a = 
2-25 > 2, therefore 1-4 < V2 < 1-5. 

(a) Continue this process one step further. 

(6) Calculate V7 to two decimal places by the same method. 

6. For what values of x do the following inequalities hold? 
(a) x* + 3x + 1 ^ 0. (c) ' l 



S6. 
(b) X* - x + 1 ^ 0. (d) Sx - 2 ^ a* 



x + 

X 



7. Prove that the arithmetic mean of two positive quantities 
a, 6 is not less than the geometric mean Vab, i.e. that 

-±r > Vab. 
State when the equality sign holds. 

8. The quantity | defined by - = ( +-)is called the harmonic 

5 2 v» 6/ 
mean of the two positive quantities a, b. Prove that the geometric mean 
is not less than the harmonic mean, i.e. that Vofi ^ %. 
When does the equality sign hold? 

9.* Show that the following inequalities hold, if a, b, c are positive: 
(a) a 1 + 6» + c» g ah + be + ca. 
(6) (a + b)(b + c)(e + a) ^ 8a6e. 
(c) o 2 6* + 6«c» + cV ^ abc (a + b + e). 

549 



550 MISCELLANEOUS EXAMPLES 

10. The numbers «,, x* *, and a ik (t, k = 1, 2, 3) are all positive. In 
addition, o J]k g 3/ and a^' + xf + * s a ^ 1. Prove that 

a^xf + 2ai 2 a: 1 a; 8 + . . . + a^V g 3Jf . 

11.* Prove that if the numbers %, a 2 a n and &„&,,..., &„ satisfy 

the inequalities Oj ^ a a ^ . . . ^ o n , & t ^ b 2 2: . . . S 6„, then 

12. Prove the following properties of the binomial coefficients: 

<<)+«GM;) + --- + -C)-»*"- 

(c) 1 . 2g) + 2 . 3 (J) + . . . + (n - 1)»(*) = »(»- l)2»-«. 

.«'+iG)+iGD+-+.-TiO-^r- 

13. By summing 

v(v + l)(v + 2) ... (v + ft + 1) - (v - l)v(v + 1) . . . (v + k) 

from v = 1 to v = n, show that 

Sv(v + l)(v + 2)...(v +fc ) = "<" +1 )---( re + fe+1 ) . 

v- j e+2 

14. Evaluate I s + 2 3 + . . . + n 3 by using the relation 

v> = v(v + l)(v + 2) - 3v(v + 1) + v. 

15. Evaluate 

, . 1 . 1 , . 1 

( a > , „ „ + i— jr— ; -. + ••• + 



1.2.32.3.4 n{n + l)(n + 2) 

/m l _L. * -I. X J- -L. l 



1.3 2.43.5 n(n + 2) 

1 1 ' 



1.2.4 2.3.5 n{n+ l)(n + 3) 

16. Find a formula for the n-th term of the following arithmetio pro- 
gressions: 

(a) 1, 2, 4, 7, 11, 16, . . . . 

(6) -7, —10, —9, 1, 25, 68, . . . . 



MISCELLANEOUS EXAMPLES 551 

17.* Show that the sum of the first n terms of an arithmetic pro- 
gression of order k is 

aS k + 6S t _, + ...+ pS, + qn, 

where S„ represents the sum of the first n v-th powers, and a, b p, g 

are independent of n. Evaluate the sums for the arithmetic progressions 
of Ex. 16. 

18.* Prove the binomial theorem 

(o + 6)» = a B + ("V" -1 * + ("V"""* 6 ' +••• + &" 

by mathematical induction. (See also Chap. Ill, p. 201.) 

19. Find 

(a) lim (— + .— + . . . + )■ 

»-^.\1.2 2.3 n(n+l)J 

(6) lim ( — h — h ...+ V 

'»->.\1.2.3 2.3.4 n(n + l)(n+2)/ 

/ 1 1 1 \ 

(c) lim ( -n- + ,.— — + . . • + -rif J. 



20. If Ss f = 0, prove that lim S a^ Vn + » = 0. 

i-o »— >■» «-o 

21. Prove that lim " = 0. 

»->«2 n 

22. Prove that lim (n + 1)5 = 0. 



23. Prove that lim tfn* = 0. 



(2» + 1),, 



24. Prove that lim -y/(n* + n) = 0. 

* — >■« 

25. Use Cauchy's convergence test to show that the following sequences 
converge: 

1 

(a) a n = . 

n 

... n + 1 

(6) c = — L- . 
n 

(c)*«„=. + 1 1 j + 2 1 ! +... + n V 

26.* Show that the limits of the sequences (c), (d) of the previous 
example are reciprocals of one another (so that the limit of the sequence 
(<*)isl/e»). 



552 MISCELLANEOUS EXAMPLES 

27.* Prove that the limit of the sequence 



V2, V2 + V2, - v / 2 + V2 + V2, ... 
(a) exists, (6) is equal to 2. 

28.* Prove that the limit of the sequence 

exists. Show that the limit is less than 1 but not less than £. 
29. Prove that the limit of the sequence 

- X +-..+ 1 



n+1 2n 

exists, is equal to the limit of the previous example, and is greater than 
i but not greater than 1. 

30. Obtain the following bounds for the limit L of the two previous 

i 37 ^, , 57 

examples: — < L < — 

60 60 

31.* Let a v 6, be any two positive numbers, and let a, < 6,. Let 

a ' = a 1 + b l ' 6 ' =Vo » 6 i' 
and in general 

a n-i T- ° B -i 

Prove that the sequences a„ a 2 , . . . and b lt b 2 , . . . converge and have the 
same limit. 



32.* If a n > 0, and lim V+> = L then lim jy = L 



33. Use Ex. 32 to evaluate the limits of the following sequences: 



(a) yn, (b) v'fn* + » 4 >, (c) ^/(~)- 

34. Use Ex. 33(c) to show that 

re! = ra B e _n o n , 

where a n is a number whose ra-th root tends to 1. (See Chap. VII. Appendix, 
p. 363.) 

x -4- 2 

35. Prove that lim — — - = 2. Find a 8 such that for I x I < 8 the dif- 

z-^.0 x + 1 

a: + 2 
ferenoe between 2 and is. in absolute value, (a) less than A> (6) less 

a: + 1 
than 10 1 00> (c) less than e, e > 0. 



MISCELLANEOUS EXAMPLES 553 

36. (a) Prove that lim a = -. Find a 8 such that for | 1 — * | < 8 
«_>i x + 1 2 

the difference between - and is, in absolute value, less than e, e > 0. 

2 x + 1 

Do the same for (6) lim V(l -f x 3 ); (c) lim 



z— >2 *— »-o a; 

37. Prove that (a) lim - (1 + a:) ~ 1 = i. 
*->o x 2 



(6) lim V* + i( Vx + 1 — Vx) = J. 

2 — ^-w 

38. Prove that lim (cos to) 2 "* exists for each value of x and is equal to 

m — >•» 

I or according as x is an integer or not. 

39.* Prove that lim [lim (cos im\ a;) 2 ™] exists for each value of x and is 

equal to 1 or according as x is rational or irrational. 

40. Determine which of the following functions are continuous. For 
those which are discontinuous, find the points of discontinuity. 

{a) f(x)=t±^±^f, /(0) = 0. 
sinx 

(6)/(x) = a;5 + 5 ^ + 3a: , /(0) = 0. 
smx 

(c) f(x) = lim (cosnx) 2 "*. 

m — >■» 

(d) f(x) = lim [lim (cosmilx) 2 "]. 



41. Let /(x) be continuous for ^ x ^ 1. Suppose further that f(x) 
assumes rational values only, and that f(x) = £ when x = £. Prove that 
/(a) = J everywhere. 

42. Has the function 

fix) = 2 sin 3* + 10 cos5x 

any real zeros f 

43.* If /(x) satisfies the functional equation 

/(*+»)-/(») + /(*) 

for all values of x and y, find the values of /(x) at the rational points and 
prove that, if /(x) is continuous, f(x) = ex, where c is a constant. 

44.* Prove a converse of the theorem of uniform continuity; namely, 
that if /(x) is uniformly continuous in the half-open interval a < x SJ 6, 
then f(x) tends to a unique limit asi->j (which may be taken as the 
value of /(a)). 



554 MISCELLANEOUS EXAMPLES 

45. Plot the following graphs, and express the equations in Cartesian 
co-ordinates: 

(a) r=*a+b cos 6 (Limacon). 

(6) •—=—^— s (Ellipse). 
2 — cos8 

. . 2a sin a 6 ,— . ,. 
(c) r = (Cissoid). 

cos 6 

(d)r= ******«»* (Folium of Descartes), 
sin* 9 + cos'o 

46.* Show that the equation of an ellipse with one focus at the origin is 

= k 

l — ecos(e — e )' 

47. Let c be the complex number x + iy represented by a point in a 
Cartesian co-ordinate system. Plot the ourves 

c— t 



(«) 
(&)* 



o + t 
e — a 



2. 



= k, a, |3 complex constants, 
c- p 

(c) |c»-l| = *. 

48. Let Cj, c s be two complex numbers. Prove that 

(o) \c 1 ±c 2 \^\c 1 \ + \c i \. 
(b) I^ical^lcjl-Kl- 

49. Prove the equality 

I "a + c a | * + | <H - e a | « = 2 | c, I s + 2 1 c, |* 
and state its geometrical interpretation. 

50. Prove that (oos6 + » sine)" = cos»6 + » sinnG by mathematical 
induction. 

CHAPTER II 
51.* Prove directly that the derivative of the functioD 

f(x) = x" sin -. x =*= 0; /(0) = 
x 

exists at every point and is equal to 

— cos - + 2x sin -, x 4= 0; at x = 0. 

X X 

Show that although f'(x) is not continuous at x = 0, nevertheless the 
mean value theorem still applies and the property of Ex. 67 below holds 
good. (See pp. 199, 200 of the text.) 



MISCELLANEOUS EXAMPLES 555 

62. Draw the graph of the Amotion 

/(x) = x sin -, x dp 0; /(0) = 
x 

and find its derivative for x 4= 0. Show that its derivative does not exist 

at x = 0, but that the difference quotient ^-^ ^-/ as x -> has the 

x 

upper and lower limits 1 and — 1 respectively. (See p. 199.) 
53. Investigate the behaviour of the function 

f(x) = x sin - + a? sin -, x #= 0; /(0) = 
x x 

with regard to differentiability. 

64. Prove that the derivative of the function 

f(x) = - sin x, x 4= 0; /(0) = 1 
x 

exists at every point and is equal to 

fix) = — — sin x + - cos x, x #= 0; /' (0) = 0. 

X 2 X 

Show that f'(x) is continuous, and find f"(x). 

55. If f{x) is continuous and differentiable for a g x £J 6, show that if 
/'(a;) ^ for »:£*<!; and /'(x) ^ for $ < x ^ 6, the function is never 
less than/(§). 

56.* If the continuous function f(x) has a derivative /'(x) at each point 
x in the neighbourhood of x = £, and if /'(x) approaches a limit L as x — *■ 5, 
then /'( 5) exists and is equal to L. 

57.* If /(x) possesses a derivative f'(x) (not necessarily continuous 
at each point x of a ^ x ^ 6, and if /' (x) assumes the values to and M) 
it also assumes every value ft between m and M . 

58. If /"(x) ^ for all values of x in a ^ x ^ 6, the graph of y = /(x) 
lies above the tangent line at any point x = §, y = /($) of the graph. 
(The curve is convex upwards.) 

59. If f"(x) ^ for all values of x in a ^ x ^ 6, the graph of y = y /(x) 
in the interval 1,^1^1, lies below the line segment joining the two 
points of the graph for which x = x x , x = x s . 



60. If/"(x) => 0, than /(**+*) g /<*»> + /(**>. 



61. Given /(x) = $x* — x* + 1, find a number <5 such that for every 
h less in absolute value than S and every x in the interval — J Sa x 5> i 
the following inequality holds: 



A 



JL 
loo 



556 MISCELLANEOUS EXAMPLES 

62. Differentiate directly and write down the corresponding integra- 
tion formulae: (a) x 11 *; (b) tana:. 

63. Evaluate 

(o) lim J- (l +*+■•• + 4-Y 

(6) lim I ( 1 + sec* - + sec a - + . . . + seo a — Y 
»— >.» » \ 4n 4ra 4»/ 

64. Prove that 

2"+ 1 (n!)« 



(a) T 1 (x> - l)»(fa = J?; (6) (-D" f 1 (*" - l)»«fe = 



(2m + 1)! 
65. Show that 



1 /-"+ 1 & 1 

+1 J. * 



v+ 1 J x v 

1 v 

and 



> + » + .. . + i<r*<i + i + ... + . » 



2 3 n ./, a; 2 n— 1 



1 1 f v dx 

Prove that the sequence 1 + -+... H / — , v=l, 2, .... is a 

2 v Ji x 

decreasing sequence and is bounded below. 

66.* Let f(x) be a function such that f"(x) S for all values of z, 
and let u = ti{t) be an arbitrary continuous function. Then 



1 [ a f(u(t))dt>f( l f a u(t)dt). 
ajQ \ctJo ' 



67.* If a particle traverses distance 1 in time 1, beginning and ending 
at rest, then at some point in the interval it must have been subjected 
to an acceleration =£ 4. 



CHAPTER m 



68. Differentiate the following functions: 

/ a \ gtan'x + logsinz^ 

(6) (x + 2) 4 (1 - a^'V + l)" 7 . 
x 3 sina; — a; 5 cosa; 



(«) 



a^ tana; 



69. What conditions most the coefficients a, (3, a, b, c satisfy in ordei 
that 

ax+ g 
V(aa? + Zbx + e) 

shall everywhere have a finite derivative which is never zeroT 



MISCELLANEOUS EXAMPLES 557 

70. Sketch the graph of the function 

y = (**)*> y(0) = i. 

Show that the function is continuous at x = 0. Has the function maxima, 
minima, or points of inflection? 

71. Among all triangles with given base and given perimeter, the 
isosceles triangle has the maximum area. 

72. Among all triangles with given base and given vertical angle, the 
isosceles triangle has the maximum area. 

73. Among all triangles with given base and given area, the isosceles 
triangle has the maximum vertical angle. 

74.* Among all triangles with given area, the equilateral triangle has 
the least perimeter. 

75.* Among all triangles with given perimeter, the equilateral triangle 
has the maximum area. 

76.* Among all triangles inscribed in a circle, the equilateral triangle 
has the maximum area. 

77. Prove the following inequalities: 

w^rb- x>0 - 

(6) e» > 1 + log(l + x), x> 0. 
(e) e* > 1 + (1 + x) log(l + x), at> 0. 
78.* Let a, 6 be two positive numbers, p and q any non-zero numbers, 
p < q. Prove that 

[6a'+(l-e)6g] 1/>> 5;l 

[6a« + (1 - Q)b"f lq 

for all values of in the interval < < 1. 

(This is Jensen's inequality, which states that the p-th power mean 
[00*+ (1 — Q)V*f v of two positive quantities a, 6 is an increasing function 
of p.) 

79. Show that the equality sign in the above inequality holds if, and 
only if, a = 6. 

80. Prove that lim [8o» + (1 - e)^] 1 * = a"* 1 -*. 

81. Defining the zero-th power mean of a, 6 as o*6 1 -*, show that 
Jensen's inequality applies to this case, and becomes (a 4= 6) 

a 96i-« > [0 O « + (1 — e^ 9 ] 1 '" according as q ^ 0. 

For 8=1, a?&-« ^ 6a + (1- 6)6. 

82. Prove the inequality 

«j,i-« ^ 8a + (1 — 0)6, 

o, 6 > 0, < 6 < 1, without reference to Jensen's inequality, and show 



558 MISCELLANEOUS EXAMPLES 

that equality holds only if a — b. (This inequality states that the 0, 1 — 6 
geometric mean is less than the corresponding arithmetic mean.) 

83. If <p(x) -*■ oo as x -*- oo , show that log<p(x) is of a lower order and 
e* te> of a higher order of magnitude than <p(x). 

84, If the order of magnitude of the positive function f(x) as x •* oo 

is higher, the same, or lower than that of x m , prove that / f(^)d^ has the 
corresponding order of magnitude relative to a; m+1 . "'" 

/(5)<Z5 relative to 

j v ~y x^x mo xuxiuwxug imiuuuxlH J W ; 

(a) -^ (c) *e»*. 

(&) e». (d) log*. 

86. Prove that if f(x) is continuous and 

/(*) = [ X f(t)dt, 
then f(x) is identically zero. 

87. Prove that 2 w;* -1 = v - 1 — . 

i-i (x - If 

88. Show that ' = u n (x]e x l*, 

where u n (x) is a polynomial of degree n. Establish the recurrence relation 

M n+i - *»n + «»'• 

89.* By applying Leibnitz's rule to 

- (e»'/2) = xt**!*, 
ax 

obtain the recurrence relation 

"n+i = *"» + »«„-i- 

90.* By combining the recurrence relations of Ex 88, 89, obtain the 
differential equation 

u," + mt n ' — nu n = 

satisfied by «„(*). 

01. Find the polynomial solution 

u„(x) = x n + ai*" -1 + . . . + o, 

of the differential equation «„" + »u B ' — nu n = 0. 



MISCELLANEOUS EXAMPLES 559 

1 d» 



92.* If P n (x) = _L *!. (a;2 _ i)», prove the relations 



(a) P '— x *~ l P » 4. ( n + 2 )* p , » + 2 

(a) ^» +i ~ 2^+"D p » + ^+r F - + ~r f - 

(&)P„ +I , = *P„'+(»+l)P B . 

(c) £ ((*» - 1)P„') - n(n + 1)P„ = 0. 

93. Find the polynomial solution 
of the differential equation 

£ «* - i)p n o - «(» + i)p„ - 0. 

94. Determine the polynomial P„(x) = (a? — l) n by using 

the binomial theorem. ^" re! ^ 



95 

that 



* Let W*) = (n)^ 1 ~ x ^~ n ' » = 0» 1. 2 p. Show 

1=SW*). , g) 



* = ^ U X„Jx). 

n-ip 



»-* 



(f) 



CHAPTER IV 
Perform the integrations in Ex. 96-101. 
96. f] + <{ X dz. 99. f Xt ~ l dx. 



\>x 
VV" + 1) "*" *""' J xV(x*" - 1)' 



m <• dx 



-ry-^ dX. 100. / 



98 /* xdx 101 f *** 

' J ^(l + x)- V(l + x)' ' J x(x + 1) . . . (x + n 

Evaluate the integrals in Ex. 102-107. 

coa n xdx. 103. / cos' 39 sin* 68 i8. 



56o 



MISCELLANEOUS EXAMPLES 



104 



l 



1 x* n dx 



105. f 
•4) 



1 a* n -*dx 
V(l - x*)' 



V(l — X 2 )' 

106. f x*V(\ - 3?)dx. 107. f ^(1 _ x*f*dx. 

Jo J o 

Obtain recurrence formulae for the integrals of Ex. 108-112. 

108. fx<>(logx) m dx. 111. fe ax aiahbxdx. 

109. fx n e ax einbxdx. 112. je ax coshbxdx. 

110. /V'e * ooabxdx. 



results 



/dx 
— ; in three different ways and compare the 
V(a a — x 2 ) 



114.* Let P„(a;) = — — (a? - l) n . Show that 
" 2»»! dx n 

f P n (x)P m {x)d* = 0, if m * n. 

T 1 2 

115. Prove that / iy(a:)<fo:= — — 5 . 

J-l 71+1 

116. Prove that f x m P n {x)dx = 0, if m < n. 

117. Evaluate f x"P n (x)dx. 

Test whether the improper integrals in Ex. 118-131 oonverge or 
diverge. 



118 



r" dx 
i i 

'" Jo V(ox — X 2 )' 
/•" dx 
119 - h *V(*-1)* 

120. jf^)"** 

121. jf X^D" 

-CO 

122. / «-*B»»(]oga;)»<te; 
•A) 

123. / log sinztfz. 
, f -log 



dx. 



124 



'sinxdx. 



/ x log sinztix. 
Jo 

/ e-"dx. 

J—<X> 

r 



x^-ig-x'dx. 
t/2 a;m(fa! 



'o (sins)" 
r m dx 

J 1 + x* sin 2 *" 



X 00 itfa; 
1 + X s sin'a 
^ r m x*dx 
J 1 ■+- aP sin* 



MISCELLANEOUS EXAMPLES 561 

132.* If f — dx converges for any positive value of a, and if f(x) 

tends to a limit Lasx^O, show that / J ->— - — ^— dx converges and 
p Jo x 

has the value L log -. 
a 

133. By reference to the previous example, show that 



(a) / ix = log -. 

J x a 

/•°°cosaa; — cosSa; p 

(6) / — <&: = log -. 

134.* If / -Q dx converges for any positive values of o and b, and if 
J a x 
f(x) tends to a limit M as x -*■ 00 and a limit i as x -* 0, show that 

f-/(-0^«W *.-(£_ Jf, kg S. 
Jo x a 

135. Obtain the following expressions for the gamma function: 



T(n) = 2 f* x u *- 1 e-*'dx, 
Jo 

Xi / IN" -1 
flog- 1 dx. 



CHAPTER V 

136. Plot the following curves and find their equations in non-para- 
metrio form: 

. . 5aP oat 8 

(a) x = — — ,, V = 



1 + *»' " 1 + « 5 
(6) x= at + b sint, y = a — 6 cost. 
137.* Show that the two families of ellipses and hyperbolas, 

°* J y*— = 1, for X < 6, 

a 2 _ x T 6 2 - X 

-| ? — = 1, for a < t < 6, 



a 2 _ T &2 — T 

are confocal and intersect at right angles. 

138. Find the pedal curves (see p. 267, Ex. 11) of the following: 
(a) the ellipse x = a cos 6, y = 6 sin 6 with respect to the origin; 
(6) the hyperbola x = cosh 6, y=b sinhO with respect to the origin; 

(c) the parabola y 2 = 4px with respect to the origin; 

(d) the parabola y 2 = 4px with respect to the focus. 

19 CB798) 



562 MISCELLANEOUS EXAMPLES 

139. Show that the tangent to an ellipse is equally inclined to the 
focal radii drawn to the point of contact. 

140. Show that the tangent to a hyperbola is equally inclined to the 
focal radii drawn to the point of contact. 

141. A constant length I is measured off along the normal to a para- 
bola. Find the curve described by the extremity of this segment. 

142. Find the area bounded by the loop of the curve 

x 5 + y b — Sarty 2 = 0. 

143. Find the area enclosed by the curve 

a?(x* + y 2 ) 2 (6 2 a^ + aV) = (a a — & 2 ) 2 6 2 a;\ 

144. Find the length of arc of the epicycloid 

x = (a + 6) cost — 6 cos — — — t 
b 

y = (o + 6) sin* — 6 sin -~ — t 

reckoned from the initial point t = 0. 

145. Prove that the radius of curvature at a point of the polar curve 
r = /(9)i3 

r-+(S)T 

d6 2 W 

146.* If the curvature of a curve in the a^-plane is a monotonic 
function of the length of arc, prove that the curve is not closed and 
that it has no double points. 

147. Find the moment of inertia of a rod of length L 

(a) with respect to its centre; 
(&) with respect to one end; 

(c) with respect to a point on the line of the rod at a distance d from 
the centre; 

(d) with respect to any point at a distance d from the centre. 

148. Find the equation of the curves which everywhere intersect the 
straight lines through the origin at the same angle a. 

149. Find the equation of the curves whose normal is of constant length 
k. (The " length " of the normal is the length of the portion of the 
normal intercepted between the curve and the a;-axis.) 

150. Show that the only curves whose curvature is a fixed constant 
k are circles of radius \jk. 

151. Find the equation of the curves whose centre of curvature lies on 
the x-axis and whose radius of curvature is therefore equal to the length 
of the normal. 



MISCELLANEOUS EXAMPLES 563 

152. Find the equation of the curves whose radius of curvature is 
equal to the length of the normal but whose centre of curvature does not 
lie on the a-axis. 

153.* Obtain the formula for the length of a curve in polar co-ordinates. 



CHAPTER VI 

154. Deduce the integral formula for the remainder B n by applying 
integration by parts to 

/(* + A) - /(*) = /"/'(* + t)*t. 

•'O 

155. Integrate the formula 



R n =- f\h - T)»/ <n+1, (* + t)*t, 
to! Jo 



and so obtain 



A", 



K = /(* + *) ~ /(*) - V(«) - • • • - „y/ (*>• 

156.* Suppose that in some way a series for the function f(x) has 
been obtained, namely 

f(x) = a t) +a 1 x+atf?+ ... + a„x n + B„{x), 

where a , a v . . . , a n are constants, B n (x) is to times continuously differen- 

tiable, and Bn ^ -+ as x -* 0. Show that a k = £-±-± (fc = to), 

x n fc! 

i.e. that the series is a Taylor series. 

157.* Find the first three non-vanishing terms of the Taylor series 
for sin 2 a; in the neighbourhood of * = by multiplying the Taylor series 
for sina; by itself. Justify this procedure. 

158.* Find the first three non-vanishing terms of the Taylor series 

sina; 
for tana; in the neighbourhood of x = 0, by using the relation tana; == — -, 

and justify the procedure. 

159.* Find the first three non-vanishing terms of the Taylor series 
for V cos a; in the neighbourhood of x = 0, by applying the binomial theorem 
to the Taylor series for cos a;, and justify the procedure. 

160. Find the first four non-vanishing terms of the Taylor series for 
the following functions in the neighbourhood of x = 0: 
(a) a;cota:. (c) seoa;. (e) ef- 

(6) Vsjnx . (d) e*". (/) log sina; — loga:. 

Vx 



564 MISCELLANEOUS EXAMPLES 

161. Find the Taylor series for arc sinx in the neighbourhood of x = 

by using 

r* dt 
are sinx = / ,- 

Jo Vl — fi 

(Cf. p. 203, Ex. 5.) 

162.* Find the Taylor series for (arc sins) 2 . (Cf. p. 203, Ex. 5.) 
163. Find the Taylor series for the following functions in the neigh- 
bourhood of x = 0: 

(a) sinh- 1 ^ (6) f er*'dt. (c) f ^- dt. 

Jo Jo * 

164.* Estimate the error involved in using the first n terms in the 
series in Ex. 163. 

165.* Two oppositely charged particles +e, — e situated at a small 

distance d apart form an electric dipole with moment M = ed. Show that 

the potential energy (a) at a point situated on the axis of the dipole 

M 
at a distance r from the centre of the dipole is — (1 + e), where e is 

approximately equal to — 
4r 2 ' 

(6) at a point situated on the perpendicular bisector of the dipole is 0; 

(c) at a point with polar co-ordinates r, relative to the centre and axis 

of the dipole is — — (1 + s), where s is approximately equal to 

— (5 cos 2 6 -3). 
8r a 

(The potential energy of a single charge q at a point at a distance r from 

the charge is q/r; the potential energy of several charges is the sum of 

the potential energies of the separate charges.) 

166.* Find the first three terms of the Taylor series for f 1 + - ) 

in powers of -. 

x 

167. Evaluate the following limits: 

(a) lim z|"(l+ -)*-«"]• 

(c)* lim x [(l + *)*- e log (l + ?)"] . 

(d) lim (™y. W lim ( s ^y". 

168.* Show that the osculating circle at a point where the radius of 
curvature is a maximum or minimum does not cross the curve. 

169. Find the maxima and minima of the following functions: (a) \x\, 
(b) xsin(l/x). 



MISCELLANEOUS EXAMPLES 5^5 

CHAPTER VTI 

170. Show that the length of the ellipse x = a cost, y = 6 sin< is 

/■v/2 o 2 — 6 2 

s = 4a I VI — e 2 cos 2 tdt, where e 2 = ; 

JO a 

Calculate the length of the ellipse for which e = \ to four significant figures, 
by using Simpson's rule with six divisions. 

171. Expand the integral of Ex. 170 as a series, and estimate the 
number of terms necessary for accuracy to four significant figures. 

172. Evaluate / ° g ^ ' dx, using Simpson's rule with h = 0-1. 

Jo x 

173. The hypotenuse of a right-angled triangle is measured accurately 
as 40, and one angle is measured as 30° with a possible error of i°. Find 
the possible error in the lengths of each of the sides and in the area of the 
triangle. 

174.* By considering / log (a + x)dx, a > 0, show that 

•'l/a 

a(oe + 1) . . . (a + re) = a n n\ re", 

where a n is bounded below by a positive number. Show that a n is mono- 
tonically decreasing for sufficiently large values of n. (The limit of a n 
as re -* » is l/r(a).) 

, , re,! re,! . . . nA , 

175. Find an approximate expression for log j , wnere 

n 1 + n l + ... +»j = n. 

176. Show that the coefficient of x n in the binomial expansion of 

1 1 

= is asymptotically given by — ==. 

Vl-x v™ 



CHAPTER VIH 

* °° tx 

177. Prove that if S a„ 2 converges, so does S — . 

„_1 v-l v 

178. If a is a monotonic increasing sequence with positive terms, 

when does the series - + + - - + . . . converge? 

Oj a x a^ a^a % a 3 

179.* If the series S a v with decreasing positive terms converges, 
then lim na n — 0. v ' 1 

n — y «> 

00 TT 

180. Show that the series S sin- diverges. 

u 



566 MISCELLANEOUS EXAMPLES 

181.* Prove that if Sa„ converges and if 6,, 6 a , 6 3 , . . . is a bounded 
monotonio sequence of numbers, then ~Zafi v converges. 

182.* Prove that if 2a„ oscillates between finite bounds and if 6,, is 
a monotonio sequence tending towards zero, then Sa„6„ converges. 

183. Discuss the convergence or divergence of the following series: 

(a) S tJl. (6) S (-l>*°° s (8/v>. (c) S ^ 9 . 

V v V 

«£) S !^- 6 . (e) S (- 1 )" C0Sv9 . (/) S ( - 1),/Sinve . 

V V V 

184. Find the sums of the following derangements of the series 
l-i+$-l+l-i+... ioi log2: 

(a)i-i-i+i-*-i + i-A-A+ •••• 

(6) 1 + * + *— * — i— i+ + + — 

1851 For what values of a do the following series converge? 

(a) 1 +- i — H .... 

w 2" 3 4" 5 6* 

(6) 1 + 1 — 1 + 1 + 1—1+ + — 

w 3" 2" 6" 7 a 4" 

186. Find whether the following series converge or diverge: 

(a) l + i-i+i'+ *-* + *+!-*+ + -.... 
(B)l+i— f+i+i— f+t+i— f+ + — 

187. Show that 

(") S 7^ converges. 

00 log(v + 1) — logv 
(6) £ M , ',, converges. 

„ =2 (logv) 3 

» 1 2 3 ... v 

(c) S — r converges if a > 1 and diverges 

W „_ 1 (a+l)(a + 2)...(«+v) 8 

if a^l. 

CO J 

188.* By comparison with the series 2 — , prove the following test: 

c = l ^ 

If lo gwl a »D > 1 + s for every sufficiently large n, the series 2a„ 

converges absolutely; if ^fo ° < * ~ e f or ever y 8uffioien % ^S 6 
», the series 2a„ does not converge absolutely. 



2 / 1 V 
189. Show that the series 2 1 1 — —i-\ converges. 



MISCELLANEOUS EXAMPLES 5&7 

190. By comparison with the series S — , prove the following test: 

The series S | a v | converges or diverges according as 

log(l/»| a nl) 
log logn 

is greater than 1 + e or less than 1 — s for every sufficiently large ». 

191. Derive the »-th root test from the test of Ex. 188. 

192.* Prove the following comparison test: if the series 26 v of posi- 
tive terms converges, and 

| g n+l 



I d« 






from a certain term onwards, the series So,, is absolutely convergent? 
if £&,. diverges and 

a n b n 

from a certain term onwards, the series Za„ is not absolutely convergent. 

193. Obtain the ratio test by comparison with the geometric series. 

00 1 . 

194.* By comparison with S — , prove Raabe s test: 

The series S | a v \ converges or diverges according as 



"(r^i- 1 ) 



I °n+l I 
is greater than 1 + e or less than 1 — e for every sufficiently large n. 

195. Bv comparison with 2 — -, prove the following test: 

J v(logv) a 

The series 2 | a v | converges or diverges according as 

nlogJlM^ -I- 1 -) 

is greater than 1 + e or less than 1 — e for every sufficiently large ». 

196. Prove Gauss's test: 

where | iJ„ | is bounded, then S | a„ | converges if (i > 1, diverges if |i g 1. 

197. Test the following series for convergence or divergence: 

/ ^ a ,«(«+!) , a(q+l)(a+2) 

W ^ + p(P+l)^P(P+D(P + 2) 

... . , a.B , a(a+l).&(P+l) , a(«+ l)(a + 8). P(p+ 1XP + 8) . 

W + I7y 1.2. Y (Y+1) 1.2.3. Y (T+l)(Y+2) 



(6) 


(2v)! ' 


(e) 


v 1 

" V*' 


(d) 


v(-l)' 



568 MISCELLANEOUS EXAMPLES 

00 1 
198. (o) Show that the series 2 — converges uniformly for x ^ 1 -+- e. 

(6) Show that the derived series — 2 — — converges uniformly for 
* ^ 1 + e. v°> 

199.* Show that the series £ , a > 0, converges uniformly for 

c S x :£ 2tt - c. v ° 

200. The series 

<e + 1 3 Va; + 1/ 5 Ve + 1/ " 
converges uniformly for s ^x ^ N. 

201. Find the regions in which the following series are convergent: 

(a) Ex-'. (e) X%> a < 1. 

</>s£ «>i. 

1*" 

(A) 2 * 

v» 1 — x" 

202.* Prove that if the series £ converges for x = x , it converges 

for any x > x a ; if it diverges for x = x , it diverges for any x < x . Thus, 
there is an " abscissa of convergence " such that for any greater value 
of x the series converges, and for any smaller value of x the series diverges. 

203. If £ -" converges for x = x , the derived series — £ — — — con- 
verges for any x > x . 

204. If a„ > and £a„ converges, then 

lim 'Za v x v = £<v 
x—yi-a 

205. If a„ > and £a„ diverges, 

lim 'Za^x" = 00. 

206.* Prove Abel's theorem: 

If £a„X" converges, then £«,,£" converges uniformly for ^ x ^ X. 

207.* If Sa^X" converges, then lim £<ve" = Sa^". 

X—&-X-0 

208. Find the rational functions represented by the following Taylor 
series: 

(a) x + x 2 — x 3 - x* + x 6 + x e h + • • • • 

(6) 1 + 2* — 4a? — 5a* + 7a: 8 + 8a:' 1- + • . . • 



MISCELLANEOUS EXAMPLES 569 

209. Show that 

w i + 5 + i + "- 1 

(6)i + J^_ + 1 - 3 - 5 - 7 + ...= * V8. 
v/ 22. 4. 62. 4. 6. 8. 10 2 

1 » 

210. Let z = re l9 = »-(cos0+ i sin 6). Prom the expansion = S z v , 

show that 1 ~ z "=° 

1 — J-CO80 S „ „ 

= S r" cosv0 



and 



1 — 2rcos0 + r 2 ,_ 
r sin0 



S r"sinv0. 



1 — 2rcos0 + r a „_„ 



CHAPTER IX 

211.* Using the expression for the cotangent in partial fractions, ex- 
pand tzx oot izx as a power series in x. By comparing this with the series 
given on p. 423, show that 

s l - < iy»-* (27c)am B 

212. Show that 

S 1 _ (— l)""- 1 ^ 2 " 1 — l)n 2m B 

v=1 (2v-l) 2m_ 2(2m)! *"' 

213. Show that 

» (_!)■»_ (_ i)«»(2 2 "' — 2)7t 2m R 
v-l"^™" - 2. (2m)! 

214. Prove that 






a 6 

+ Z 12 



215. Using the infinite products for the sine and cosine, show that 

. x , /sinz\ " (-l)-i22-i^ 

(a) log I ) = — 2 ^— * . 

\ x / „=i (2v)!v 

(6) log cos* = -^ ^ *>• 

19* (1798) 



570 MISCELLANEOUS EXAMPLES 

216. Using the infinite products for the sine and cosine, evaluate 

(a) f . f • 5 . f • 9 • tl • if • • • • 

m o 1 4 1 U U U 

(0) ^.§.f.$. 9 • 15 • 15- 

217. Express the hyperbolic cotangent in terms of partial fractions. 



CHAPTER XI 

218. Find the curves whoso tangent ia of constant length a. (The 
"length" of the tangent is the length of the portion of the tangent 
intercepted between the curve and the a;-axis.) 

219. Find the curves which are orthogonal to the family y = ce kx . 

220. If « denotes the length of arc of a chain measured from a point 
at which the tangent is horizontal, the form of the chain is determined by 
the differential equation 

d 
dx 



,™-l<P& 



x 



Show that the equation of the chain is y = c cosh -fa. 

221. Integrate the equation for the electric circuit 

|jj + pi = E, 

where E = E a sin<o<, and u., p, E w u> are constants. 

222. A particle falls towards a point which attracts inversely as the 
cube of the distance and directly as the mass. Find the motion and time 
of descent if v = and x = a at t = 0. 

223.* Integrate y = — xp + x*p\ where p = X 

224. Integrate y = p + logj). 

225.* Solve the difference equation 

"»+» + 2aM n+i + 6 "» = °» 

where a, 6 are constants, by putting u„ = X n . Show that the solution can 
be expressed in the form u„ = ar-f + P»»"» where r„ r a are the roots (sup- 
posed distinct) of the equation X 2 + 2aX +6=0. Show that the form 
of the solution when 6 = a 2 is u n = cc(— o) n + p»(— a) n . 



ANSWERS AND HINTS 



CHAPTER I 
§ 1, p. 13. 

1. (d), (e). Show that x satisfies an equation of the type 

X s + a,?* + . . . 4- a e = 0, 

where a v . . . , a 6 are integers; prove that * is then either irrational or 
an integer. 

2. Use the irrationality of sin 60° = V3/2. 

4. Write ax 1 + 26a; + c as al x + - ) H • 

\ a) a 

7. If a >0 and 6 a — oc 5^0, it is possible to make ax i +2bx-\-c=0 
for some value of x if, and only if, 6 a — ac = 0; then use Example 6. 

8. The cosine of the angle between two straight lines is ^ 1 in absolute 
value. 

9. Use Schwarz's inequality. 

10. Square both sides and then use Schwarz's inequality. The sum 
of the lengths of two sides of a triangle is not less than the third side. 

§§ 2, 3, p. 26. 

2. (a), (d), (e), (g) odd; (6) even. 

3. (6), (c), (A) monotonic; (a), (d), (e), (I), (m) even; (d) and (e) identical. 

§ 4, p. 28. 

2. (n + 1) (2» + 1) (2» + 3)/3. 

3. (c) Expand (1 + 1)" by the binomial theorem. 

4. (a) n(n + l){n + 2)19. 

(b) Sum from v = 1 to v = n. n/(n + 1). 

v+ 1 v 

(c) Sum from v = 1 to v = n. n(» + 2)/(n + !)*■ 

(v + l) 2 v a 

5. 3; 193. 

7. J(2ra* + 3» ! — 11» + 30). 

671 



572 ANSWERS AND HINTS 

§ 5, p. 36. 

1. (a) 1; (6) 333; (c) 333,333. 

2. (a) 0; (6) oo; (c) 6; (d) o /6 ; <e) 1/3. 

4. 19. 

5. (a) 6; (6) 10; (c) 14. 

6. (a) 25; (6) 2500; (6) 250,000. 
9. (a) 0; (6) no; (c) yes; (e) 30. 

15. The greatest of %, . . . , a k . 

16. 2. 

17. Use the fact that n/2 n -> 0. 

§ 6, p. 45. 

1. (a) For every number M, no matter how large, there exists aD n 
such that | «„ | > M . 

(b) There exists a positive number e such that for every number M 
there exist numbers n, m greater than M for which | o„ — a m | ^ s. 

5. Error is less than ; e = 2-71828 .... 

n(n\) 

§ 7, p. 49. 

1. (a) 6; (6) 15; (c) J; (d) 3. 

3. Limits (a) and (b) do not exist; limit (c) exists and is equal to 1. 

§ 8, p. 55. 

3. (a) 1/60; 1/600; 1/6000. 

(6) 1/10(1 + 2| 5-1 1), &o. 

(c) 1/120(1+ | 5|) 3 , &c. 

(d) 1/100; 1/10000; 1/1000000. (e) 1/10; 1/100; 1/1000. 

4. (a) 1/600; e/6. (6) 1/400; e/4. (c) 1/77600; e/776. (rf) 1/10000; e 2 . 
(e) 1/100; e. 

5. (a), (6), (c), (i), (g) continuous; 

(e) discontinuous at x = 2, 4; 



(/) 


„ x = 3; 


(A),(fc),(m) „ 


„ x = (ra + J)tc; 


W, (j) 


„ a; = wtc; 


(0 


„ a; = nn, n 4= 0. 


Appendix I, p. 70. 




1. (a) Upper bound 


_ £|* ( * lower = 0, upp 


(6) 


i * — l * 

— 2» " — x ' 


(c) 


9 * 2 * 

— 10' " — 3' 


(d) 


19 * 1 * 

— 10' » ~~ 3> 


(*) 


= 2* „ = 0, 


The quantities marked 


* belong to the sequence 



> 0, lower = 0. 

0,* „ = 0.* 



_ A 
— 2> 


tf 


_ 1 

— 2 


3 

— 2' 


99 


1 

— 2 



= 1, „ = 0. 



ANSWERS AND HINTS 573 

2. Divide the interval into a finite number of sub-intervals by points 

o = x , x x , x t x„ = b so close that | f(x) — f(x) \ < e if x and x lie in 

the same sub-interval. Join adjacent points x = x it y = /(a; f ) by straight 
lines. 

3. The expression —-\x—x t \ + -\x— x t ^ | has the slope zero 

2 ^ 

outside the interval (x t - ly x t ). Add suitable terms of this kind. 

t + *-f|*-2|+|*-S|-l|*-S|. 

4. (a) e/6; (6) e/na"- 1 , » > 0; (c) e 8 /2. 

Appendix II, p. 75. 

2. (a) r= a; (6) r = 2a eos(<p — <p ); (c) r = a/cos (<p — <p ). 

3. oos26 = cos 2 8 — sin 2 0, sin20 = 2 sin© cosO; 

cos36 = 4 cos 3 9 — 3 cos0, sin30 = 3 sin — 4 sin 3 0; 
cos50 = 16 cos 5 — 20 cos 8 + 5 cosG, sin50 = 16 sin 6 — 20 sin 8 
+ 6 sinO. 

4. (a) — 6i; = n, r = 3; 6 = tt/2, r = 2; = 37t/2, r = 6. 

(J) 1 + V3 + t(l - V3); = 7t/4, r = 4V2; = ti/3, r = £; 
6 = 77t/12, r=2V2. 

(c) 2; = tc/4, r = V2; = 7tt/4, r = V2; = 2ti, r = 2. 

(d) 2 - 2» V3; = 5tc/6, r = 2; = 6jt/3, r = 4. 

(e) ±1; = 0, r = 1; = 0, r = ± 1. 

(/) ± (^ + ^} 6 = W2, r = 1; = rc/4, r = ± 1. 

( ? ) {VV2 + 1 + t-v/^2 - 1}/V2; = tc/4, r = V2; 
= tt/8, r = «(/2. 

(h) — v/18 (V3 + »)/2; 8 = 7n/4, r = 3V2; 
6 = 77t/6, r = (3V2) a/3 = ^/18. 

(*) 1, (-1 ± »V3)/2; = 0, r = 1; = 0, ^, ~, r = 1. 



(Z) y'2{\/V2 + 1 + *VV2— 1}; 8 = tt/2, r = 16; 
6 = it/8, r = ± 2. 
5. Note that e" satisfies the equation x n — 1 = 0; then factorize 
x n — 1. 

CHAPTER H 
§ 2, p. 87. 

1 . Use formulae of § 2 and the basic rules: 70/3. 

2. Required area may be regarded as the difference between the area 
under the line and the area under the parabola, taken between the points 
of intersection of curve and line: 10V5/3. 

3. V5/6. 



574 ANSWERS AND HINTS 

4. J(o» + 4bf*. 

5. (a) {(1 + b) 1 *"- — (1 + a) 1+a }/(l + a); (6) — (cosaft — cosaa)/a; 
(c) (sin a& — sin aa)/a. 

7. (6 4 - a 4 )/4. 

8. l/(n + 1). 

§ 3, p. 109. 

1. For every number a there exists an e such that for every positive 
number 8 there exists an x for which 

I x - 5 I g S and a - fW-f&) ^ e _ 

x-l 

2. (a) —!/(*+ I) 2 ; (6) -2x/(x* + 2) 2 ; (c) -4a;/(2a; 2 + l) 2 ; 

(d) — cos a: /sin 2 a:; (e) 3cos3x; (/) — asinaa;; (g) 2siua;cosi; 
(h) —2 cosaisina:. 

3. (a) 5 has any value; (6) 5=^ + ^/2; (c) S=^?!±3|l±fl). 

§ 4, p. 119. 

2. (a) J; (6) J. 

§ 5, p. 121. 

1. ~= 0-785. 
4 

§§ 6, 7, p. 130. 

a + b ' f/a n + a"-^ + . . . + b n \ r , - 

1. (6) 5 = -f - ; (c) 5=V( „ + I ) ; (<£) ^^ /a6 ' 

3. (a) /„ = aW»/(l + 1/n), lim /„ = a; 

n — >■» 

(6) 7 n = a"+V(« + J )> lim /„ = for — 1 g a ^ 1, » for a > I. 

4. | JP(a) — /(a;) | S -I f | /(s + <) — /(*) I *• Use tne uniform con- 

28 J _ j 

tinuity of /(#) in a :£ x ij 6. Also, we may write 

F(x) = 1 { J" /(«)* +f X+ *f(t)dt}, 

where c is a fixed number. 

5. Express the integrals as limits of sums, using equal subdivisions 
of « g » ^ 6, and applying Schwarz's inequality (p. 12) to these sums. 
Another method is to integrate {fix) + tg(x)} 3 ^ and use Ex. 6, p. 13. 

Appendix, p. 135. 

1. Let <f(x) = f\x) where f'(x) S: 0, <p(a:) = elsewhere. Let 

4> (x) = f'(x) — 9 (x); then ij/ (x) ^ 0. Consider; <p(x)dx, I ty(x)dx. 

J a J a 



ANSWERS AND HINTS 575 



CHAPTER in 
§§ 1, 2, p. 143. 

1. /'(!)= 1, /"(!)= 8, /'"(1)=36, /"(1)-9Q, /"(l) - 120, 
/»<(1) = 0, / rii (l) = 

2. 0. 

, „ ad — be 

3. (a) a; (6) 175 ex"; (c) 2(& + ex); (d) j^Tf? 

. 2x*(a$ — ab) + 2x{ay — ac) + 2(6y — ftc) . 
te ' (aa? + 2|3a; + y) 2 

4,(1 + ^)_ 
U (I - a*) 2 (l + **)» 

4. (a) *■(*) = a„x n + (a„_, + na n )x n ~ l 

+ {a„_ 8 + (n - l)(a„_, + ,m n )}a:"- 2 + . . . . 

(6) F(x) = ?» *» + («„-! - ««„ - 1 ) -r n - 1 + 
c \ c / 

Kr 2 _ (n _ l)a„_, C \ - n(n - \)a n (^LZ^> }*—+.... 

5. (a) 2 cos 2a:; (6) — 1/(1 + sin 2a;); (c) tana + a/cos 2 *; 

/7v « ,-. • « . , > sina: , cos* 

(d) -2/(1 - sin2.r); (e) H 

x 2 x 

6. sec 3 a; + sec a; tan* a:. 7. 24 sec 5 a: — 20 sec 3 a; + sec a;. 

8. cosa: (cosec 2 a; — 6 cosec 4 a;). 

9. 24 sec 5 a; — 20 sec'a; + seca; — cosa:. 10. «>. 
11. aa: 2 /2 + bx. 12. 00^/3 + bx* + ex. 

13. x s + x> + X s + X s + x. 14. -(1/a; + 1/2** + l/3a?). 
15. a^/3 — 1/x. 16. a siax — 6 cota:. 

17. 3a~72 — 7 cosa; — 5/2x 2 — 9 tana:. 18. seca;. 

§ 3, p. 152. 

1.4. 3. y X {l — (n- l)a:}/»a;(l + x)K 

4. oos % x/2Vx — 2Va; sina; cosa:. 5. 1/Va;{l — V xf. 

6 (! — tan *) + 3a! ( 1 + tan 2 a:) 
3ar* /3 (l - tana:) 2 

7. (arc cosa: — arc sina;)/V(l — x 2 ). 

8. 2/(1 + a: 2 )(l — arc tana:) 2 . 

_ 1 arc sin a: 



V 1 — a; 2 arc tana: (1 + a; 2 )(arc tana:)' 

io. L_ + * 



1 + x 2 Vl — a: 2 (arc cosa)* 
11. 0-785. 



576 ANSWERS AND HINTS 

§ 4, p. 157. 

1. S(x + 1)*. 2. 6(3* + 5). 3. 15a; 14 (3a; 8 - Go? — l)(a* - 3a? - I) 4 . 
4. —1/(1 + x)\ 5. 2a;/(l - a; 2 ) 2 . 6. an(ax + 6)"- 1 . 

1 



7. -- 



Vx*— l(x+ Vx 2 — 1) 
o ^(um — W) + 2x(an — cZ) + (6ra — cm) 

' 2V{{ax* + bx + e)(lx* + mx + to) 3 } 
9. -f(l - a;) 2 ' 3 . 10. sin 2*. 1 1 . 2x cos (a; 2 ). 

12. sina;cosa:/V(l + sin 2 a:). 13. 2 (a; sin— — - cos— Y 

\ a; 2 x xV 

2 

14. ,, . . . 15. (2a; + 3) cos (a 2 + 3a: + 2). 

(1 - a;) 2 cos 2 ( ) 

16. 3a; 2 /V{l - (3 + a~>) 2 }. 17. — 1. 18. 1. 

V2 ' 

19. — (a:^ 8 + sr^ 2 ). 2 0. -^5 cos(a; + 7) {sin(a; + 7)} V ° _1 - 

t-t actsinx , . , , .,. , 

•*1 . — —7- — . {arc sin (a cosa; + 6)} a-1 . 

V{l-(acosa;+6) 2 } x * ^ " 

§ 5, p. 166. 

1 . (o) Max. for x = — V2, min. for x = V2, infl. for a; = 0. 
(6) Max. for x = § , min. for a; = 0, infl. for x — — ^. 

(c) Max. for x = 1, min. for a; = — 1, infl. for a: = 0, ± V3. 

(d) Max. for x = -y/3, min. for a; = — ^/3, 

infl. for x = 0, ± \/6 ± V33. 

(e) Max. for x = (n + i)n, min. for x = mz, infl. for a; = n . r. 

4 

2. Max. for x = — V — p; min. for a; = V — p; infl. for x = 0. No 
maxima or minima when # s5 0. Roots are all real, or two complex and 
•one real, according as q 2 + Ip 3 g or > 0. 

3. The point (0, 1). 

4. Equation of line is (y — y )/(* — x ) = — <^(y lx ). 

5. V~i89 ft. 

6. The point dividing the line ab in the ratio \/a : -tyb. 

7. The square. 

8. The rectangle with corners x = ± a/V2, J/ = ± 6/V2. 

9. The right-angled triangle, i.e. c 2 = a 2 + 6 2 . 

10. The side of rectangle opposite to g must be at the distance 
i{V(8r 2 + A 2 ) + A} from the centre. 

11. The cylinder whose height is equal to the diameter of its base. 



ANSWERS AND HINTS 577 

13. If <p is the angle of the prism and n its index of refraotion, the 
angle of incidence must be arc sin ( n sin - ). 

14. x = (Sa f )/m. 

i 

15. Find the minimum of x v — px. 

2 

16. Find the minima of x — sina; and sinas a; in the interval 

<, x ^ - . Or, show that is monotonio in that interval. 

~ ~2 x 



18. (°i + *» + "■ + +»*)*?- 

\ n — 1 / V (^Oa . 



§ 6, p. 177. 

1.0-693. 2. logs. 3. l/zlogz. 4. 1/V(1 + a: 2 ). 

_ 1 — 2arv'l + logx cosa: 

0. — — — • 

2a:V'l + loga:(Vl + loga; — sina:) 

6. xl{x* + 1) — 1/3(2 + x). 

7 -yAs 2 +1 / 14a; _ 1 2z» \ 

' y^Tay^T+l \8(7as» + 1) 4(a; - 2) (*• + 1)/ 

11 . x = 1/X, provided X =t= 0; if X = 0, no maximum exists. 

12. (logo) 2 . aW) . a*. 

13. aMn-OoB*)' . loga jcosa;(loga;)'» + 2sm * lo g* |. 

§ 7, p. 183. 

1. (a) Keep a: fixed and differentiate with respect to y; then put y 
equal to zero. 

(6) Evaluate f(x) first for rational x, and then by continuity for irra- 
tional x. 

2. Differentiate with respect to y, and then put y equal to 1. 

3. 2315 years. 

4. (a) y = p + ce°*; (6) y = - £ + ce«*, a =j= 0; y = (3a; + c, a = 0. 



a 



(c) y = (tee"* + ce«*; (d) y = — - — eV + ce"*, y =t= a- 

Y— a 

§ 8, p. 189. 

1. sinha — sinhft = 2 coshf — —- ) sinh( J. 

cosha + coshft = 2 cosh(— - — ) coshf — - — J. 

cosht — coph& = 2sinh( —I — J sinhf — - — 1. 



57« ANSWERS AND HINTS 

/> . , . ... tanha 4- tanhft 

2. tanh(a ± 6) = — . 

1 ± tanha tanhfi 

j.\. i i i.v 1 ± ootha cothb 

ooth(o ± 6) = — = 

cotha ± cothft 

• u i //cosh a — 1\ , , //cosh a + 1\ 
smh ^=VV 2 /' 008h * a = V(. 2^} 

gtanh*+coth* 

3. (o) sinhx -(- coshz; (6) — 4 ; 

cosh4x — 1 

(c) (l + sinh2a;) oothfc + cosh 2 *); (d) l/Vfx 2 - 1)+ 1/V(x* + 1); 
(e) asinh^/Vf^cosh^H- 1); (/) 2/(1 — a 2 ). 

4. siak& — sinha. 

§ 9, p. 195. 

1. (a) Higher than X s ; (6) lower than &; (e) same as 1; (d) higher 
than x"; (e), (/) higher than x*~ % lower than xl + '; (g) same as x; 
(h) higher than x"; (j) lower than x 1 . 

2. Higher than e"*, (logx)°. same as e*^; (6) lower than eP". e*°; 
(c) bounded; (d) same as e*, lower than e*", higher than (logs)"; (e), 
(/). (?) lower than e"*. e*", higher than (log*)"; (A) higher than e* 1- '. 
lower than e* 1 " 1 "*, higher than e"*, (log x) a ; (j) same as log a:, lower than 

3. (a) Same as x£; (6) lower than (~\ ; (c) same as x; (d) same as x; 
(e) same as ir 5 ' 2 ; (/) same as a: 8 ' 2 ; (gr) higher than x N ; (A) higher than 
x l ~', lower than x; (j) lower than ( ) . 

4. Yes; 0. 5. 0, 1. 

6. lim fW = /'(0) = 0. 8, 9. Use result of Ex. 7. 

*->o x 

Appendix, p. 203. 

1- f"lg{Hxmg'*{h(x)W*(x) + f'[g{h(xm 9 "{h(x)}h'*(x) 
+ f'[.g{Mx)}]g'{h{x)}h"{x). 



(a) x^'f- n - + log*, eos A 

(6) (cos^r'f-tan^ + !58£EL*Y 

\ COS 2 X / 

(c) U 'W _ v '( x ) lo8«(«) _ 
u(x) log «(x) »(a;){log v(x) } a ° 



ANSWERS AND HINTS 



579 



4. (a) e a *[a"a? + 3na n - 1 a; a + 3n(» — l)a"- 2 a; + n(n — l)(n — 2)<x n - 8 ]; 



(6) 
(<0 



' ( S - — loga; ); 



(-1)" 
2 



{cosa: — 3 2m cos3a;}, for n = 2m; 
{3 2m+1 sin3a; — sina;}, for n = 2m + 1. 



(i) ^-Jl-[(m+fc) 2l sm(TO+fc).r— (to— fc) 2i sin(TO— fc)a;], forn=2Z; 



(-D' 



[(to + /fe) aI+1 cos (to + Jfc)a; — (to — k) n+1 oos(m — 4)x], for 



n= 21+ I. 

(e) e*[( 2 fVl) ! (2/) 22, ) cos2a; 

+ ( 2 (— 1) !+1 ( 2 f\ 1 )2 8I +Asin2a;"|=5"' 2 e i,! cos(2a;+na), 

where tana =2 (expanding (1 + 2t) n by the binomial theorem, and 
grouping real and imaginary terms). 

w-i.(!)C) (1+ ' ) -'- 

5. Let y = arc sina:. Then 

d n y _ rf"- 1 / 1 \_ rf"~ 8 / « \ 
<to" tfa"- 1 \V(1 — a; 2 )/ *c n - 2 \(1 — a: 2 ) 3 ' 2 /* 

Apply Leibnitz's rule to this last expression: 



dx n 



V 'dx»-» \(l-x^/ x= o 

= 3.(n-2)^Y * A 
V c/x"-" \(1 - a; 2 ) 5 ' 2 / 



and continue the process: 
dx" 



= 1.3.5...(2v-l).(ra-2)(n-4)...(n— 2v+2)i^*Y ~V 

„_o rfz"- 2 "V(l— x 2 ) <2 " +1> "/ 



Itn-O,** 



dx n 



■ 0; iln=2l+l, ^M 
dx" 



= 1 2 .3 2 .5 2 (2Z-1) 2 . 



j^ (arc sina;) 2 ! ='s7„, 2 [. )l 2 .3 2 (2i-l) 2 .l 2 .3 2 (2l-2k-3)K 

dx 31 lz-o i-oV'tv 



— , (arc sina;) 2 = 0. 
dx* l + l U-o 



6. Differentiate (1 + a:)" twice and put x = 1- 



580 ANSWERS AND HINTS 

CHAPTER IV 
§§ 2, 3,* p. 217. 

I. Je*\ 2. -ie-« 4 . 3. f (1 + a?) 3 '". 4. J (log x)K 

s. - _l_ Mr. 

» — 1 vloga;/ 
6. Hint: write denominator in the form (3a; — l) a + 1: arc tan (3a; — 1). 

8. Hint: 6a;/(2 + 3a;) = 2 - 4/(2 + 3a=): 2x - f log | 2 + 3a; |. 

9. arc sina; - V(l - *»). 10. log |?±i + ^1+^*5-?^}. 

II. are sin 1+i. 12. J log(a? - a; + 1) + 4s aro tan ^7^- 

2 Vd V £ 

13. 2 ar cosh (^^) + V(a; 2 - 4a; + 1). 

4. 33. 1 

14. -JjV(2 + 2* - 3z 2 ) + 3^3 arc sin _^_. 

.,2 ^ 2a; +1 tc 2 . 2a;— 1 

15. _,- are tan — ,! 16. -;- arc tan — j—. 

73 V3 V3 V3 

17. -* arotan-^" 1 "" ,if6-g a >0; — , if 6 - o a = 0; 

V(6 — a 2 ) V(6-a 2 ) a;+ a 

1 ar tanh f + a , , if 6 - a 2 < 0. 



V(a 2 - 6) V(a 2 - 6) 

18. — a*/4 - a?/3 - a; a /2 - x — log | a; - 1 1. 

1 9 . Hint: sin 3 x cos* x= sin a; cos 4 a^ 1 — cos 2 x) = sin a: cos 4 a;— sin a; cos 6 a;: 

_ cos 5 a; cos' a; 
~5~ 7 

20. ^ - 2 ™!f? + ™!?. 21 . id - x 2 )"' 2 - i(l - z 2 )'". 
22. £ aro sina; — £aV(l — a; 2 ). 23. jt 2 /32. 

24. 1 + <- 1 >". 25. 2. 26. _J_ - _J_. 

n + 1 2(1 + a 2 ) 2(1 + 6 2 ) 

a— 1 



27. J(a 3 - 6 3 ) + J(a 2 - 6 2 ) + (a - 6) + log 



6- 1 



28. i(l - cos --Y 29. Cf. Ex. 8, p. 88: l/(» + 1). 

* Here and elsewhere the constants of integration are omitted. 



ANSWERS AND HINTS 



5«i 



§ 4, P- 225. 

1. Take/= x, / = cosa;/sin 2 a;: — a/sin x + log tana;/2. 

2. Take /= a*/4, 0' = 4ar>/(l - a; 1 ) 2 : a*/4(l - x*) + i log | 1 - x* |. 

3. (a; 2 — 2) sina; + 2x coax. 

4. _J (:E 2 + i )e -x\ 5. 47c(-l) n /n 2 . 6. 0. 

7. 4(z a sina.- 2 + cosa*). 8. ^ sin4a; — i sin2a; + fa;. 

9. 3^2 sin 6a; + ^ sin 4a: + H sin 2a; + &x. 

10. Put x = cos6: aiVl-a-H- ^ - A* 2 + %*) + te arc sina;. 

1 , 1 



11. e^a: 2 — 2a; + 2). 12. — 

13. ^— -loga- 



: logx ■ 



(» — lja;"- 1 "° (» — l) 2 *"" 1 
14. ia?{(loga;) 2 -|loga; + |}. 



in 



m + 1 "°" (»» + l) 2 

16. Put x 3 = «, then use Ex. 15. 

17. Integrate by parts repeatedly. 
19. Use mathematical induction: assume that the n-th iterated 

itegral Ux) is given by 1 /"/(«)(* - m)" -1 ^, and expand the 
(71— 1)!J f X 

integrand by the binomial theorem. Then /„+i(a;) = / f n (t)dt; integrate 
each term by parts. ° 

§ 5, p. 234. 

1. log a/ 

3. log 



2— 3a; 



x+ 1 



+ 



: + 



2. log 
3 



1 — 



x + 1 2(x + l) 2 



4. \ - \ log I x + 1 1 + || log I 3a; - 5 |. 



1 */ 1 1 ~2 _1 , 4 fT+ X 3 

7. log T7 



1 2a: + 1 

; </ll ^ Tl + ilo^ + x+l) + v - 3 ^t^- vr . 

1 2a- - 1 

8. log^|a; + l|-ilog|a?-a;+l| + y3arotan- v , 3 -. 

9. W ., + log yTT^+ t arc tana;. 

V (* — 2 ) 

10. f log|a: + 2| +f log | a; - 1| - f log | a: + 1 1. 



11. -J + log^ 



x+1 
x-1 



■ J arc tana:. 



582 



ANSWERS AND HINTS 



,„ , V3, *»+V3x+l 

12. i arc tana; + — log — -^ \- i arc tan(2a: + V3) 

12 3? — VZx + 1 

+ J arc tan(2a: — V3). 

„ ,, 1-1 , V2 a; 3a: 2 + 2 a 

13. i log — — + _ - aro tan -r~. 14. — Z — f arc tanx. 

° x + 1 3 V2 2a;(a* + 1) 2 



§ 6, p. 241. 



1. — 



1 + tan ; 



(2 tan * + 
2 
-, — 
V3 



/2 tan * + 1\ 



4. *(tan 2 |- cot 2 g + ho g [tan||. 5. log 



6. _j_ arc tan - V2. 
V2 2 

c 1 .2 tana: 

o. -— .— arc tan — , — . 

2V3 V3 



tan + 1 
2 



tan - — 1 



n 1 . tana; 

7. __- arc tan -, — . 
V2 V2 

i 

+ log cos a;. 



2 cos 2 a; 



10. " log 

V2 6 



tan * — 1 + V2 
2 



tan - — 1 — V2 
2 



II * i™, cos2a; — cosa; + 1 , 1 A 2 cosa: — 1 



r lo g 



+ ; 



4 ° (cos a a; + cosa; + l) s 2V3 

1 ,2 cosa; + 1 

— — -r- arc tan -, — ■ — . 

2V3 V3 

l 2. - x ^/ x i _ 4 _ 2 ar cosh s- 
1 



arc tan ' 



V3 



13. - a:V4 + 9a^ + ^ ar sinh = *. 



14. 2 arc tan 



lx-2 



15. i V{x* + 4xf - (x + 2) VV + 4a;) + 4 ar cosh ?-+-?. 

16. V»- V(l-*)+-^log 



17. log ac. 



Vl + , 



Vl — a; 



Vl + a;+ VI- 



(Va:- Vj)(Vl-x+ Vj ) 
(Vx+ Vj)(VT^z- Vj) 

+ V(l-a?). 



ANSWERS AND HINTS 583 



18. J ar cosh(2a: —2a+l)+ V(x - a) 2 +(x—a)— 2Vx - a. 



2 



19 '8FI) {V( - 8,, - V( *" w 

§ 8, p. 254. 

I. Div. 2. Conv. 3. Conv. 4. Conv. 5. Div. 
6. Conv. 7. Conv. 8. Div. 9. Conv. 10. Conv. 

II. Conv. 14. (a) For < * < 1. (6) For < s < 2. 
15. Yes. 

Miscellaneous Examples IV, p. 255. 



1. Put are sinx = t: ie" csinx (x + Vl — x 2 ). 

2. £ cos** — \ cos's. 

3. *{(logs)» - 2 log* + 2}. 4. J log * ~ °™* . 

5. Put V(l -«-**)=<: x - V(l - e- 2 *) + log{l + V(l - e-*»)}. 

6. 0. 7. 0. 10. 0. 

12. Consider the function 1/x for the interval lgi^2. Subdivide 
the interval into n equal parts and form the lower sum as in Chap. II, § 1 
(p. 76 et seq.). This turns out to be oc n . Now let n -*■ 00. The result is 
log2. 

13. Compare with 1/V(1 — x>) at x = 0, 1/n, 2/n, .... (n -l)/n: rc/2. 

14. Evaluate 

limlog"M= lim iriogl + logfl-^)...+ ... + log(l-^^- 1 )l ) 

using the definition of the definite integral. 

15. 1/(1 + a). 



CHAPTER V 

§ 1, p. 267. 

1. (x* + y*)* = a»(z» ~ y*) a - 

2. Take e as rotating with constant velocity, and measure the time 
so that at time t = the point P is in contact with the circle C: 
a! =(iJ + r)cose-»'co8{(iJ + r)6/r}, y=(ii + r) sin0 — r sm{(B + r)Q/r}. 

3. x=2R cos0(l — cosG) + B, y = 2iJ sin 6(1 — cos6). 

4. x = (i? — r) oos6 + r cos{( J B — r)Q/r}, y=(R—r) sin6 
— rsin{(iJ — r)6/r}. 

6. Take rectangular co-ordinates so that the origin is at the centre of 
and the point P lies on the x-axis at time t = 0: ar" a + #"* = £!"*. 



5«4 ANSWERS AND HINTS 

7. x = &rf/(l + «»), y = 3<rf»/(l + < a ). 
10. a = are tan f^'" 9 ^. 

11. - - / /(y ^ + "^ '> - w-N) ?w+ go/o+zw- jy> 

12. (a) itself; (6) the cardioid of the circle with diameter PM, 
having its vertex at P. 

§§ 2, 3, p. 290. 

1. |(6 6 ' a - o«/ 2 ). 2. 3a a /4. 3. £a 2 (6 2 » - 6, 3 ). 4. 67riP>. 
5. 6rw a . 6. tc(1 + £e 2 )- 7. £7t(a 2 + 6 2 + a; a ). 

8. x = 5 + «(1 - s/2B + s 2 /32.R 2 )(l - a/16iJ), 

y = #(«/£ - « 2 /16iJ a ) 3 ' 3 (l - s/8if), for g 5 g 16iJ. 

9. x=2a arc cos(l — s/4as) — (1 — s/4a)V{s(l — s/8o)/2o}, 

y=s — s*/8a, for ^ s ^ 8a. 

10. a = V(4/9 + a) 3 - 8/27. 11. 6B. 

12. (a) |a{arsinh9 + 6V(1 + 6 2 )}. 

m 
(c) 85(1 - cos£8). (d) a{J(0 3 - 6„») + 8 - 6 }. 

13. (a) \(\ + 4z a ) 3 ' a : min. £ at x = 0. 

(6) (a 2 sin 2 9 + & a cos 2 <p)/a&: if a > b, min. 6/0 at 9=0, it, 
max. a/b at 9 = n/2, 37t/2. 

14. p = 1/Vt. 

17. Vol. ra- a (A 2 - h t ) - Jtt(V - V)- Surface 2tt(A 2 - A,)r. 

18. If p is the radius of circxe and r the distance of its oentre from the 
line, the volume is 27tVp a , the surface area 4jt 2 rp. 



71 

20. A = its. 



19. tc^j — a: ) + ~(amh2xi — sinh2a; ). 



21. y = — ar cosh- + V(l — a; 2 ) + const.; a = log f— Y 

* \x / 

x= ef, y= — ar coshe~» + V(l — e 2 *) -f const. 

22. Let da, ds' be the lengths of arc, I, I' the total lengths, A, A' the 
areas, and k, k' the curvatures of the curve and the parallel curve respec- 
tively. Then 

ds' = (1 + pk)ds; K = */(l + pi); 

4' = A + lp + np 3 ; l'=l+ 2np. 

23. (a) ? = r(sin9 2 — sin 9 1 )/(9 2 — 9,), 

i) = — r(cos9 a — cos 9 1 )/(9 2 — 9J, 
where 9j, 9 2 are the 6-co-ordinates of the extremities of the arc. 



ANSWERS AND HINTS 585 

(6) 5 = (x t ainhx 2 — x t sinhx, — cosha; 2 + cosha^)/(sinha; 2 — sinna?]) 
r\ = {2(32 — x 1 ) + sinh2zj — sinh2a; 1 }/4(sinhx 2 — sinha:!), 

vehere (x v y,), (a; 2 , y 2 ) are the extremities of the arc. 

24. (a 2 + |3 2 )(& - a) + § (0 s - a"). 

25. (a) sinhzj — sinha:! + |(sinh 3 a; 2 — sinh 8 ^), 

(6) (x 2 * + 2) sinha;, — (a;, 8 + 2) sinhx, — 2x 2 cosha: 2 + 2a;, cosh*!, 
if :g x x ^ a; 2 . 

§ 4, p. 298. 

, dx rsin(2</r) . t 

1 . — = — — . 1 — !—L — sin - ; 

dt 2V(P— r* sin* (t/r)) r 

d*x _ _ P cos(2t/r) + r 2 ai n l (t/r) _ 1 t 

dfl~ V(Z 2 — r^sin 2 ^,"-)) 3 r COS r' 

2. Horizontal. 

3. u — v /(l + ksv ), t = s/v + £fcs 2 . 

4. (a) a; = 4 arc tane' — 7t; a; = tc. 

5. (a) t= -j-— - (y a V(y <s -y) — «/ 3/a are tanV{y/(y — y)}+i*y<>)- 
(b) V{2(i.if(l/JJ- l/y )}; (c) J§^. 

j n e) 2 

6. 6 = at, r =» , where a = — -~- y/ck; 

1 — e coaat k? 

period = 2 * = 2 * ira • jfc 3 ' a . 

F (J. - e) 2 c 1/s 



CHAPTER VI 
2. 0-182. 3. Impossible; series not valid. 



1 - (1 - a;)i/<-+» 

o — — • 



51, 


P- 


319. 




1. 


0-28. 


$2, 


P- 


325. 




2. 


1 : i 

1 — X 

1 . < 




1 + X 


§3 


P 


330. 




1. 


1 + iz- 



= 



x 

(1 + x) 1 '"- 1 -* - 1 



1 V2 

4<r+teF -i<iJ< ~Ts' 

2. 1-5; error just over 6%. 3. 1 + |x; | a; | < 0-3, 



586 ANSWERS AND HINTS 

4. 1 + £*-!**; ^x 10-». 

5.(o) 1 + *; L(l -l)x 10-*. 
n 2n\n J 

(6) i + * + i.(I_i)^ l(i-l)(l-2)xl0-». 
» 2n \n / on \ra / Vra / 

6. 00100. 7. (a) 0-9999; (6) 5-0133; (c) 9-8489. 8. 0-515. 

9. x 2 - - + — + - (-128 cos(20a;) ). 

3 45 8! 

Sj.2 7^4 a-6 

10. 1— — + _ + f _ (243 oos(39a!) + cos (foe)). 

11. -i*» -£**-<&«• 

— 16 — (17 + 248 tan 2 (0x) + 756 tan 4 (6a;) + 840 tan 6 (0ar) 
8! +315 tan 8 (0a;)). 

12. x + £a* + A* 6 

+ 16 — (17 + 248 tan' (6*) + 766 tan 4 (fte) + 840 tan' (6a;) 
71 + 315tan 8 (0a;)). 

*3. \x>+ -fat + igx* 

+ 16 - (17 + 248 tan 2 (Ox) + 756 tan 4 (6*) + 840 tan 6 (0s) 
8! +315 tan 8 (6a;)). 

14. l-x*+h*--e- e ' x '. 

2 3! 

15. 1 + Ja; 2 + i& 

+ - (720 seo'(6a;) — 840 sec 5 (6a;) + 182 sec" (6*) - sec (6a;)). 
61 

1A Xr _ -J^yS 8 ~8 

au. 3 o. 45 x B45 x • • • » 

17. -go; + seoar* + xei^o 3 - + • • • • 

18. a:- fa? + V* 8 + - (-60 + 24 log 1 + 6a;). 

8 6 4! (1 + e*; 6 



19. 1 + a: + ^r 2 — ^x« + — e^^ (cos 6 (6a;) — 10 oos 3 (0a;) + cos(0a;) 

— 10 sin (0a;) cos 8 (0a;) + 15 sin (8a:) cos (0a;) + 6 sin 2 (0a:) cos (0a;)). 

20. x+ix 3 ; 0<x< it/4. 

21. (a) y = a? + a* + 2a; 6 + . . . ; (6) y = 1 — a; 2 — a: 4 — 2a; 6 — ... ; 
(c) y = 3? + a* + 

§ 4, p. 335. 

1.2. 2.4. 3.0=8/3, 6=16/3, c = — 5/3, d=— 5/3. 

4. Third order and also zero order at (0, 0); zero order at (J, J). 

5. Third order at (0, 0). 



ANSWERS AND HINTS 587 

7. Take P as origin and the tangent to the curve at P as x-axis. Let 
the co-ordinates of Q be (x, y). Then the centre of the circle in question 

lies on the w-axis at the point -n = - A : use Ex. 6. 

' 2 V 

8. Take axes as in Ex. 7; let the slope of the curve at Q be y'. Then 
the two normals intersect on the y-axis at the point y] = y + — Now 

v"(o) y 1 

write y — Z-AJ 3? + . . . , and let a; -*- 0. 
2! 

1 1 -i- i/zyM* 

9. At a point P where p = - — is a maximum or mini- 

y" 

3v'v" 
mum, we necessarily have y'" = — — Take axes as in Ex. 7; then 

(1 + y' 2 ) 

y"'(0) = 0, so that the equation of the curve in the neighbourhood of 

a;=0isy= — a^ + ax 1 + • • • • The equation of the osculating circle 

1 2p 

is y = — x 3 A-bx* Ar . . . , and the contact is at least of order 3. 
2p 

10. Minimum at x = 0. 

Appendix, p. 341. 

1. raa"- 1 . 2. 1/6. 3. 1/30. 4. 2. 5. 1. 

6. Write expression as cota;/oot6a;: 1/5. 

7. 1/2. 8. 1/3. 9. Take logarithms: 1. 
10. e. 11. 2. 12. —2. 



CHAPTER VII 
§ I, P- 348. 

1. (a) 3-14; (b) 3-1416. 2. -89. 

3. 0-93. 

§ 2, p. 355. 

1. Error < — 03 metre, < 0007%. 2. 0-693. 3. 1-609438. 

4. 3-14159. 

§ 3, p. 360. 

1. 10755. 2. 4-4934. 3. 1-475. 

4. 0, 1-90, —1-90. 5. 1-045. 

6. Write equation in form x = 1 + 0-3X 3 — 0-lx 1 ; 1-519. 

7. —1-2361, 3-2361, 6-0000. 



588 ANSWERS AND HINTS 

CHAPTER Vni 

i 

1 . Use the fact that - 



§ 1, p. 376. 

1 1 1 



v(v + 1) V V + 1 

2. Split up l/x(x + l)(x + 2) into partial fractions: in the result 
substitute x = 1, x = 2, . . . , x = v in turn and add. 

4. Convergent for a > 0. 

5. Put 2a„ = A. For every positive s, \s n — A\ < e if ra is greater 
than a certain m. Write 

8 t + ... + s s _ a t + ... + a m , N — m s m+1 + . . . + s s 
N N N N—m 

and let JV -*■ oo . 

6. Yes. 7. No. 

§ 2, p. 382. 

1. Convergent. 

2. Prove first that n\jn n g 2/ra 2 when n > 2: convergent. 

3. Divergent. 4. Cf. Chap. Ill, § 9, p. 189: divergent. 

5. Note that (logn) logn = W og<Iogn) and log (logn) > 2 when n is 
large: convergent. 

6. Convergent. 7. l/(re+ I) 2 . 

8 - Err0r== (^TT)i( 1+ n-|-l + (,+ 2) 1 (n+3) + ---) 

< (nTTJ! V 1 + «T+1 + (n+~l)» + ' " 7 

< * _* < 1 



(n + 1)! x _ 1 re . n! 

71+ 1 

9 • E^or = (-»l i l^« + (¥+W + ••• 



(n + l)"* 1 (» + l)"** (» + l) n+s «(» + 1)" 

Error = --+-1 + ^t-? + Now for n > 1, 

n + 2 < f (n +1), n + 3 < f (» + 2) < (|) 2 (n + 1), . . . ; 



hence 



Error <^+i(l + f +(!)'+. ..X^r 1 . 



ANSWERS AND HINTS 589 

dx 



12. Convergent. 13. Compare with / . 

J x(logx)« 

14. Compare with f . 

J x logx (log loga;) 1 * 

16. Use Schwarz's inequality. 

O 3n+3 1 n-t-1 1 3n | 

17. 1 + f - f + . . . _ _£_ = 2 --3S„-= r l -, 

^ 3 ^ 3n + 3 ^v r-1 3v „.. Ta v 

then use the formula on p. 381, 

1 + i + i + • • • + - = l°g» + G + z„, 
n 

where lim e„ = 0. 

n — >ao 

18. Take the sum from v = I to v = mn: 

§§ 3, 4, p. 397. 

/0 if x = 
3. (a) lim /„(*) = 

»-».» ^1 if 



if * 4= 0. 

10 
(b) 



(0 if * == 
) Km /„(*) = (a>0). 

»->■« (1 if «=# 

/•l /.l 

Convergence is non-uniform, and lim / f n (x)dx = I lim f n (x)dx. 

(0 if \x\ <1 

4. lim/„(*) = jf if 1*1 =1 

"^" ll if |*| >1. 

9. Consider lim -^(1 — a; 2 ") for -1 < x < +1 and lim -y^l — J/*") 
for — 1 < y < -f 1. 

1 . Let e > 0. Divide up the interval by points x = a, x v . . . , 
x m = 6 into sub-intervals of length less than e/SM. At each point x t we 
can choose n ( so large that | /„(*,) — Sm( x i) I < e /3 when n and m > n { . 
Let iV be the greatest of n , n x , . . . , n m . Then prove by the mean value 
theorem that in each sub-interval the inequality | f n (x) — f m (x) \ < e 
holds when n and m > N. 

§§ 5, 6, p. 409. 

Note on Ex. 1-20: in most of these problems the ratio test is effective, 
but for Ex. 12-15 the root test is preferable. 

1. | x | < 1. 2. | x | < 1. 3. \x\ < 1. 

4. | x | < 1. 5. | x | < 1. 6. — co < x < + oo. 



590 ANSWERS AND HINTS 

7. | * | < 1. 8. | a: | <1. 9. |a;| <1. 

10. |*| <1. 11. |*| <1- 12. | * | < 1/a. 

13. |*|<1. 14. |*| <1. 15. — oo <*< +<». 

16. |*| < 4. 17. |*| <1. 18. | * | < 1 or a, which- 

ever is the greater. 

19. |*| <1. 

20. Note that l/n 1 * 1 " 1 lies between nr 1 and nrh | * | < 1. 

21. £ V^r. 
„=o vl 

00 1 * ** *" _ 1 " *» 

^.Z . — — — — — — — . • • — — ••• — __ _ 2^ — • 

2 3 4 ra+2 * a „= 2 v 

oo / l)y— 12 2 " - * 

23. Write sin 3 * = J - J cos 2*: S - '—— * 2 ". 

F =l ( 2v )! 

oo /_ 1W021/ — 1 

24. 1 + £ v — ^ a 2 '. 

,_i (2v)! 

00 / l w— l/o~\2i> 

25. S ^— ^ K -^~ (15 + 3 2 " - 6 . 22"). 

„_ 8 32(2v)! ^ 

,, la* 1.3*" . , 5 fr 8 ) 2 -" 1 1.3...(2v-3) 

26 -^ + 2^ + 2^T + -'- = ^ + i 2 i^T-2^4T^(2^2,- 

27. 1-4142. 

28. (a) 1 - _L_ + _2_ L_ + _ 

3 . 3! 6 . 5! 7.7! 

(6) _ + _L + 1 - + 

V 2 320 3 . 2 12 

(c) 1 -^ + p-i + ^- + -"- 

(d) Put * = 1/t: ~ - - -1 + i - + 

1 ' ' 10 10 6 24. 10 9 

m& 1 It* 

29. (a) * + ** + |. (6) ** - a? + ig.. 

, 3? , 13* 8 , 19** .,. . x 4 

(c) * + — + H (<*) ^ — ^r- 

w 2 24 48 3 

31. |*| < p. 32. /(*) = 4e? - x - 1. 

Appendix, p. 423. 

1 . Break off the series at the »-th term; then 
1 *+J_* 2+ J^_*3 + ,.. + Ll 3 ---( 2 "- 3 )*n<l-V ( l-*)^l. 

2 2. 4 2.4.6 2. 4. ..2m 

Put x — 1: the partial sums all :§. 1. 



ANSWERS AND HINTS 591 

2. Use Ex. 1. Show that the greatest error occurs when x = I and 
that it can be made less than e. 

3. Write | * | = Vt* = V{1 - (1- <»)}: then put x = \ — & in Ex. 2. 

4. The substitution x = a + (6 — a)t transforms the function f(x) 
into a function <p(<), ^ t ^ 1. Approximate to <p(<) by a polygonal func- 
tion ty(t) to within e/2 (cf. Ex. 2, p. 70). Represent ty(t) as a sum of the 
form a + bt -\- 2c f J t — t a |. Approximate to this by a polynomial (cf. 
Ex. 3) and replace t by its expression in terms of x. 

7. If there were only a finite number of primes, the identity would be 
valid for any positive s, in particular for « = 1. (Multiplication of absolutely 
convergent series.) 

8. First prove by induction that 

n— 1 

(1 - x) n (i + x* v ) = 1 - x 2 ". 

v=0 



CHAPTER IX 
§§ 1, 2, p. 437. 



a. 
2 



" " In + 1\ n 1 

3. S sinva = imaginary part of S e'" a : sin f — ^— Joe sin - a/sin - 
*=l k=o \ 2 / 2 2 

4. Use the formula o„(a) = J(l — e < «)- 1 (e- <na — e'"* 1 "") on p. 436. 

1 /•" 

5. Evaluate — / c k (a)doc, and then use expression for « m (a) in 

terms of c k (a). 
§| 3, 4, p. 446. 

gair g — air /■ 1 » / JW -\ 

1. (a) 1 ~— + S -j— — - (a cosvx — v sinva:) k 

7T (2a r=1 n a + v 2 J 

8 «> (— 1)" 

(6) — 7t 4 — 48 S 5_— i. cosvz. 
15 , = i v* 

. , sinoK « , ^ r 1 , 1 2 1 . 

if o is not an integer; J sin(o — l)x + siaax + J sin(a + l)x, if a is an 
integer. 

, „ 6— a 1 ™ /sin v& — sinva cosvfe— cosva . \ 
(a) — 1 — SI cosva; sinvxj- 

2-K 7t „=l\ V V / 

2. Apply the transformation x = — 77 + 2jrf to § 4, No. 2 (p. 440). 

3. B t {t) = < 8 -*+i; B 8 (<)= «»-JN a + 4<; B i {t) = <*-2l* + t*- 1 t s . 

4. .B^) has already been given in Ex. 2. By (6) of the definition in 
Ex. 3, the other expansions are obtained by successive integration. The 
constants of integration must be proved to be zero. 



592 ANSWERS AND HINTS 

5. In the results for B t (t) and B t (i) in Ex. 3 and 4 put t = 0. 

6. In the results for B^t) in Ex. 3 and 4 put I — £. 



00 / x* \ 

8. cosrcc = II (1— ,,.,)• 

v =i V (v + i)V 



CHAPTER X 

§ 2, p. 465. 

3. (a) Discontinuous on the line x = 0; (6) discontinuous for x = y = 0; 
(c) discontinuous on the line x = — y; (d) discontinuous for y = — x*. 

§ 3, p. 472. 

! (a) 8f _ 8* #_ 2 ? . 

• v ' a* V(«* + y a ) a ' «* 3 vV + y 2 '' 

(6) 8 l=2x cos (a 2 — y), ^ = —cos (a* - y). 
Bx By 

(e) ^ =■«-». %=-*.*-". 
Bx By 

<d) 8 l = - 1 8 1 = y 

Sir 2V(1 + x + J/ 2 + z 2 ) 8 ' fy V(l + x + y* + z*f 

8f = -z 

Bz V(l + x + y* + z*f 

(e) ~ = yz coste), J- = sinte), J.-=xy cos(aa). 
v ' Bx * By Bz * 

(f) V_ * Sf_ y 

U ' Bx I + x a + y*' By 1 + x* + y* 

2. (as) J- = y, J- = x, — i = — 4 = 0, — — = 1. 
Bz By Bx* By* BzBy 

Q>) 8 1=\ 8 l= l - 8 l*=-l JH- = 8% l=- X 
Bx x By y Bx* x*' BxBy ' By* y'~ 

(c) 8 1 = 1 + y * 8 1 = l + X * *?=» 2(1 + y*)y 
Bx (1 — xyf' By (1 — xyf Bx* (1 — xyf ' 

8*f = %x + y) S 2 / = 2(1 + s 2 )* 
BxBy ~(l-xyf By* (1-xyf' 

(d) 8 £=yx"-\ g=s»logz, g=y(y-l)*iM>, 

jg- = *>^(1 + y log*), g = *» (log*)'. 
&r3y 8y a 



ANSWERS AND HINTS 593 

(«) J = t^-V**), ^ = z» log^e^")], 

e 2 f 

^ = yx^e^Xyx" + y - 1), 

8H 
didv = xV ~ lelx " ) ( l + V Xo Z x + v xV lo s x )> 

0»f 

^ = xv (log*jV(W{l + *»). 

3. Differentiate qjfar 2 + y 2 ) = t('(*)<J'(y) partially with respect to x 
and with respect to y. Eliminate <p'(a: 2 -f- j/ 2 ). put y = 1, and solve the 
resulting differential equation: f(x, y) = ae' u " *''. 

§ 4, p. 479. 

. , , df z + ycosz §f_ y+x cosz 

a ' dx~~ V(a; 2 +y 2 +2a^cosz) s ' dy V(x i +y* + 2xycoazV' 

cf xysinz 

dz ~ V(x* + y 2 + 2xy cosz) 8 ' 

' 3a: V(z 2 + 2zy 2 +y 4 -z a )' 3y (z+ 2 / 2 )V(z 2 + 2z 2 / 2 +y 4 -a; a }" 



8z (z + y 2 ) V (z 2 + 2zy 2 + y 4 - i 2 ) 

df = log (l + *» 4- y 2 + * a ) + 22 '- 



8y 6V l + z 2 + y 2 + z a 

df = 2yz 

dz l + x i + y i + z t " 

(d .df = 1 df = i 

1 ; dx 2(1 + x + yz)V(x + yz)' dy 2(1 + x + yz)V(x + yz)' 

df = y 

dz 2(1 + x+yz)V(x + yz) 

2. (a) f x = z<**>r°(logz + (log*) 2 + ^j; (b) \ x = ^j? (2 log* - 1). 

5. z x = 3, z„ = 1; z r = z^ cosO + z„ sin 6, z« = —z x r sin6 + 2/ oos6. 
7. (a) ad — be; (b) 1/r; (c) 4*y. 

§ 5, p. 485. 

2. (a) -j (&)- "; (e)-l; (rf) -1. 
4 2 

20 * B798 > 



594 



ANSWERS AND HINTS 



21 19 

3. (a) - ^ (6) n; (c) 2; (d) - l l. 

4. Max. value 6, min. value —6. 5. dz/dx = — 1, 8z/8y — — 1. 

§ 6, p. 499. 

1. (a) o 2 6 2 (a 2 — 6 2 )/8; (6) -4; (c) log 2; (rf) e<">/b — 1/b — a; 

(e) w/16; (/) 4/3. 

2. 2tc. 

3. Use the fact that the figure is symmetrical; ^ of the volume lies 
above the triangle with vertices (0, 0), (1, 0), (1, 1) and below the surface 
z 2 + z 2 = l; 16/3. 

4. in(r — h)\2r + h). 







Centre of 


Moment about 


Moment of Inertia 
about 






Gravity 


x-axis 


y-axis 


x-axis 


y-axis 


■ («) 


*• 


(0, 4r/3jir) 


** 





w*/8 


m*/8 


(6) 


ab 


(K V>) 


%ab 2 


Wb 


J«6 3 


K& 


(e) 


4ab 


(0,0) 








4o6 a /3 


4a 3 6/3 


(<*) 


nab 


(0.0) 








to6 s /4 


7ta 8 6/4 


W 


lab 


««. v>) 


iab* 


K6 


o6 s /12 


« s 6/12 




Centre of 




Moment of Inertia 








Gravity 


x-axis 




about 
y-axis 


2-axis 



6. (a) o6c (Jo, J6, £c) |a&c(5 2 + c 2 ) Ja6c(c 2 + o 2 ) $a&c(a 2 + J 2 ) 
(6) fra 3 (0,0, 3a/8) 4ro 5 /15 4toj 5 /*5 4to 5 /15 

(c) \abc (ia, lb, £c) o6c(6 2 + c 2 )/60 a&c(c 2 + a 2 )/60 a6c(a 2 + 6 2 )/60 



CHAPTER XI 



§ 2, p. 509. 

1 . Cje' + c 2 e M ; e 2t — e*. 

2. Cl e-< + c 2 e- 2< ; er* — e" 2 '. 

3. Cl ei* + <yH; |(e*« - e~'). 

4. Cie~ 2 ' + c 2 te- 2 '; fer 2 '. 

5. Cje-*' + c 2 te-J«; fcH*. 



/ V3 V3 \ V3 

6. eri*l c, cos — - < + c 2 sin — 1 1 = ae~i' cos — (« — 8); 

2 a/*? 

-r- «rl* sin «; v = V3/2, ? = 4tt/V3, a = 2/V3, 8 = tc/VS. 

7. V2e-i* cos£(« + jTt); a = V2, 8 = — it/2, v = £. 



ANSWERS AND HINTS 595 

§ 3, p. 519. 

e~* 2e -2 ' (2 — co 2 ) coscot + 3co sincof 

*' ~ FT co 2 + 4 + co 2 + (1 + co 2 ) (4+~^j 

1 3 " n 

, tancoS = „, co = 0. 



V(l + co 2 ) (4 + co 2 )' 2 - co 2 

2. <H' ((co* - 1) cos V ^ I - i- (co 2 + 1) sin g 3 <) 

1 - co 2 + co 4 ~ 

(1 — co 2 ) cosat + <o sin co ^ 

1 — CO 2 + CO 4 ' 

1 5. <■> 1 

a= , tan co 6 = -, &1= -/„- 

V(l-co 2 + co 4 ) 1-co 2 V2 

3 e-i ( (co cos V - i + -J co(2co 2 - 1) sin _? ^ 
\ 2 V3 2 / 

T^coM 7 "* 

(1 — co 2 ) sincot — co cosco^ 

1 - co 2 + co 4 ' 

a, tan co8, co as in Ex. 2. 

— e~l'((l — 2co 2 ) oos|i + (1 + 2co 2 ) sinjQ 
* ' l + 4co 4 

(1 — 2co 2 ) c osco< + 2co sin cot. 
H l + 4co 4 

1 2 " n 

, tancoS = — , co = 0. 



V~(l + 4co 4 )' 1 - 2co 2 

/ u 2 _ 4 2< \ (4 — co 2 ) co sco< + 4co sin cot 

5 " 8 " \(co 2 + 4) 2 ~ S+4/ (^ + *) 2 

§ 4, p. 527. 

1 . log(l + y*) (y + V(y 2 + 1)) + 2(1 + x)- 11 * = <*• 

2. (y 3 - 2a?) /y = c. 

/•*fa> J) i« 

3. logy - / r- = c. 

J log?; — v a 

4. I/?/ = logs + 1 + ex. 

5. x= arc tan 2/ - 1 + ce- M0 """'. 

6. t/ z = sina; — cosx + cer*. 

7. cj/ 2 = e**- 1 ' 1 ". 

8. j/ 3 = a; — 2 -+- ce"*. 

9. 0032: . COSy = C. 



596 ANSWERS AND HINTS 

10. ye xl * + x = c. 

11 . x = c x e* + c 2 te l + CgPeK 

12. a; = C!e 3( + c 2 te 3t + c 3 . 

13. y = Cj cosa; + c 2 sina: + c s x cosa: + c 4 a; sina:. 

14. y = c, + Csse - * cos _- a: + c 3 e-°> sin _ a:. 

-* 2 

15. y = Cje* + c^ee x + c 3 e-« + cpcer* 

+ c 6 cosa; + c 6 sina; + c,a; sina; + c s x cos*. 

16. y = Cj + c 2 e x/0 . 

17. e-v = c, sec (a; + c 2 ). 

18. y = Cj + e^x + c 3 e°> + e 4 e-» 

19. y = ^ arc tana; + c 2 . 

20. * = r a jl + C2 

J 21og|y-l| + Cl + C2 - 

21. x=-l/( Cl t + Cl ). 

22. s = (arc sin<) 2 + Cj arc sin< + c 8 . 

23. < + c, = i v^cy' - 2&a